Abrégé

A controller is provided for generating carrier signals controlling a pulse width modulation (PWM) inverter driving an electric actuator. The controller includes an interface configured to connect to a victim circuit via sensors, wherein the victim circuit includes the power system or the electric actuator or a combination of the power system and the electric actuator, wherein the sensors are configured to measure an electromagnetic-interference (EMI) spectrum, a memory configured to store modulation frequency ranges, the measured electromagnetic-interference (EMI) spectral data of different frequency carriers, a desired EMI spectrum and a learning-based carrier design program, and a processor, in connection with the memory, configured to perform generating a frequency modulation (FM) carrier signal by solving an optimization problem, wherein the optimization problem is generated regarding a sweep time for a predetermined frequency by the learning-based carrier design program, and a PWM generator configured to generate PWM signals based on the FM carrier signal.

Classes IPC  ?

• H02P 29/50 - Diminution des harmoniques
• H02M 1/44 - Circuits ou dispositions pour corriger les interférences électromagnétiques dans les convertisseurs ou les onduleurs
• H02M 7/5395 - Transformation d'une puissance d'entrée en courant continu en une puissance de sortie en courant alternatif sans possibilité de réversibilité par convertisseurs statiques utilisant des tubes à décharge avec électrode de commande ou des dispositifs à semi-conducteurs avec électrode de commande utilisant des dispositifs du type triode ou transistor exigeant l'application continue d'un signal de commande utilisant uniquement des dispositifs à semi-conducteurs, p. ex. onduleurs à impulsions à un seul commutateur avec commande automatique de la forme d'onde ou de la fréquence de sortie par modulation de largeur d'impulsions
• H02P 27/08 - Dispositions ou procédés pour la commande de moteurs à courant alternatif caractérisés par le type de tension d'alimentation utilisant une tension d’alimentation à fréquence variable, p. ex. tension d’alimentation d’onduleurs ou de convertisseurs utilisant des convertisseurs de courant continu en courant alternatif ou des onduleurs avec modulation de largeur d'impulsions

Abrégé

An artificial intelligence-based image processing system comprises a processor that executes instructions stored on a memory to classify an input image with a prototypical part neural network including a backbone subnetwork, a prototype subnetwork, and a readout subnetwork to produce an interpretable classification of the input image including one or a combination of a classification result of the input image and an interpretation of the classification result. The backbone subnetwork is trained with machine learning to process the input image with an incomplete sequence of active convolutional layers producing feature embeddings representing features extracted from pixels of different regions of the input image. The prototype subnetwork is trained to compare the feature embeddings with prototypical feature embeddings to produce results of comparison and the readout subnetwork is configured to analyze the results of comparison to produce the interpretable classification of the input image.

Classes IPC  ?

• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• G06V 10/40 - Extraction de caractéristiques d’images ou de vidéos
• G06V 10/74 - Appariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques
• G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
• G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
• G06V 10/80 - Fusion, c.-à-d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification

Abrégé

Disclosed a decision-dependent chance-constrained optimal model for enhancing resilience of power distribution system under renewable generation uncertainty through strategically setting-up and activating dispatchable diesel generators, renewable distributed generations, battery energy storage systems, and switchable devices. By incorporating the information of decision variables, a moment-based ambiguity set is employed to depict the uncertainty arising from renewable distributed generators. By leveraging convex approximations to handle the considered joint chance constraints, the disclosed model is transformed into a tractable mixed-integer second-order conic programming problem to be solved.

Classes IPC  ?

• G06F 30/20 - Optimisation, vérification ou simulation de l’objet conçu

Abrégé

A congestion control system configured to guide pedestrians to balance congestion throughout areas of a controlled environment is provided. The congestion control system is operatively connected to a plurality of sensors and a pedestrian guidance device. The sensors are configured to capture measurements corresponding to pedestrian congestion levels at various locations within the controlled environment. These measurements are provided to a congestion control system. The congestion control system uses the measurements to determine pedestrian traffic flow at the various locations of the controlled environment. The congestion control system then uses the measured congestion levels and the determined traffic flow to determine a control command. The control command is provided to the pedestrian guidance device to configure the device to provide a guidance output to the pedestrians of the controlled environment to balance and/or reduce congestion.

Classes IPC  ?

• G06Q 90/00 - Systèmes ou méthodes spécialement adaptés à des fins administratives, commerciales, financières, de gestion ou de surveillance, n'impliquant pas de traitement significatif de données
• B61B 1/02 - Aménagement général des gares et des quais y compris les dispositifs de protection des voyageurs
• G09F 9/30 - Dispositifs d'affichage d'information variable, dans lesquels l'information est formée sur un support, par sélection ou combinaison d'éléments individuels dans lesquels le ou les caractères désirés sont formés par une combinaison d'éléments individuels

Abrégé

Power flow in a power distribution system is controlled using control commands generated based on values of system parameters. In this regard, generation prediction data, load prediction data, and real-time device status of equipment are utilized to generate scheduling data for power generation and power consumption and a network topology of the system is also obtained. The values of the system parameters are generated as an outcome of an unbalanced load flow analysis of the power distribution system using the scheduling data and the network topology. The unbalanced load flow analysis utilizes a compact multi-bus based nodal admittance model to represent relationships between nodal injected currents and nodal voltages at a plurality of non-overlapped phases of buses for a section formed by zero impedance branch connected with impedance branches in the power distribution system.

Classes IPC  ?

• H02J 3/46 - Dispositions pour l’alimentation en parallèle d’un seul réseau, par plusieurs générateurs, convertisseurs ou transformateurs contrôlant la répartition de puissance entre les générateurs, convertisseurs ou transformateurs
• H02J 3/00 - Circuits pour réseaux principaux ou de distribution, à courant alternatif

Abrégé

Feedback control for controlling a robotic manipulator includes receiving measurement signals from one or more tactile sensors and filtering the measurement signals to align them with the directions of motion of the end effector to produce an impedance-shaping signal. The feedback control determines one or more control signals to the actuators to track a reference state of the end effector based on measurements of the state of the end effector and combines the control signal with the impedance shaping signal to produce control commands. Also, the feedback control may include submitting the determined control commands to the actuators causing a change in the state of the end effector, where the state of the end effector includes one or a combination of an end effector position, an end effector velocity, and an end effector force.

Classes IPC  ?

• B25J 13/08 - Commandes pour manipulateurs au moyens de dispositifs sensibles, p. ex. à la vue ou au toucher

Abrégé

A control system and a method for controlling search agents to perform search with noisy observations and probabilistic guarantees is provided. The control system collects confidence bounds of a probabilistic classification of at least one region within at least one path of a set of paths. The control system compares aggregations of the confidence bounds of the probabilistic classifications of each path of the set of paths based on the collected confidence bounds, a first path of a set of paths is selected, for visit by a first search agent based on the comparison. The control system commands the first search agent to visit the selected first path to collect measurements associated with each region within the selected first path. The control system updates the confidence bounds of the probabilistic classifications of each region within the selected first path based on the measurements associated with the corresponding regions.

Classes IPC  ?

• G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
• G06N 20/00 - Apprentissage automatique

Abrégé

The present disclosure discloses a system and a method for controlling a vehicle in an environment. The method uses a processor coupled to a memory storing a probabilistic map of the environment relating measurements of a magnetic field and time of the measurements of the magnetic field to a probability of locations within the environment. The processor is coupled with stored instructions when executed by the processor carry out steps of the method comprising estimating a probability of the current location in the environment based on a current measurement of a magnetometer at a current timestamp by submitting the current measurement and the current timestamp to the probabilistic map, and controlling an actuator of the vehicle based on a stochastic control employing the probability of the current location.

Classes IPC  ?

• G01C 21/08 - NavigationInstruments de navigation non prévus dans les groupes par des moyens terrestres impliquant l'utilisation du champ magnétique terrestre
• B60W 50/00 - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier

Abrégé

A method for controlling a mechanical system utilizes an energy-based inverse dynamics model trained to map dynamic states of the mechanical system to corresponding torques for a plurality of actuators of the mechanical system. The method comprises collecting a feedback signal including current states of dynamics of the mechanical system. The method further comprises processing the current states of dynamics with the energy-based inverse dynamics model to produce values of the torques for the plurality of actuators and values of the potential and kinetic energy of the mechanical system. The method further comprises controlling the mechanical system based on the produced values of the torques for the plurality of actuators of the mechanical system and the values of the potential and kinetic energy of the mechanical system.

Classes IPC  ?

• G05B 13/02 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques

Abrégé

The present disclosure discloses a system and a method for controlling a mechanical system having different actuators and multiple degrees of freedom to track a reference trajectory for performing a task. The system comprises a memory configured to store an energy based inverse dynamics model trained with machine learning to map states of the different actuators to corresponding torques for the different actuators, wherein the energy based inverse dynamics model is configured to model energy of the mechanical system with a Gaussian Processes Regression (GPR) process having a matrix capturing correlations between the torques of the different actuators. The system further comprises a processor configured to process the states of the different actuators with the energy based inverse dynamics model to produce values of the torques for the different actuators of the mechanical system, and control the mechanical system based on the produced values of the torques.

Classes IPC  ?

• B25J 9/16 - Commandes à programme

Abrégé

A cascaded controller for controlling a kinetic three-phase synchronous machine comprises a current control circuitry and an active power control circuitry operatively coupled with the current controller circuitry. The current control circuitry is configured to regulate a magnitude of inrush stator current for a stator of the kinetic three-phase synchronous machine by producing a first voltage control signal causing a flow of active power in the kinetic three-phase synchronous machine. The active power control circuitry is configured to produce a second voltage control signal to reduce the active power to zero, based on the first voltage control signal. The second voltage control signal controls a phase angle of the inrush stator current such that the stator current vector is oriented to align with a magnet axis of the rotor.

Classes IPC  ?

• H02P 21/34 - Dispositions pour le démarrage
• H02P 21/18 - Estimation de la position ou de la vitesse

Abrégé

A computer-executed method is provided for IEEE 802.15.4 devices based on a suspendable carrier-sense multiple access with collision avoidance (CSMA/CA) control program and standard CSMA/CA control program for an IEEE 802.15.4 network composing of IEEE 802.15.4 devices. The computer-executed method is provided on an IEEE 802.15.4 device, and causes a processor of the IEEE 802.15.4 device to perform steps that include determining the permission of backoff suspension and the intention of IEEE 802.15.4 device to perform backoff suspension, selecting the suspendable CSMA/CA control program if the backoff suspension is permitted and IEEE 802.15.4 device intends to perform backoff suspension. The suspendable CSMA/CA control program is configured to perform active CCA within each unit backoff period and suspend backoff if channel is detected to be busy, performing a CCA when backoff completes, transmitting frame when the detected channel status is an idle state or incrementing a number of backoff (NB) when the detected channel status is an busy state, determining if a NB exceeds the macMaxCSMABackoffs, incrementing a number of retransmissions (NR) when a NB exceeds the macMaxCSMABackoffs, and discarding frame when a NR exceeds macMaxFrameRetries.

Classes IPC  ?

• H04W 74/0816 - Accès non planifié, p. ex. ALOHA utilisant une détection de porteuse, p. ex. accès multiple par détection de porteuse [CSMA] avec évitement de collision

Abrégé

A computer-executed method is provided for IEEE 802.15.4 devices based on a suspendable carrier-sense multiple access with collision avoidance (CSMA/CA) control program and standard CSMA/CA control program for an IEEE 802.15.4 network composing of IEEE 802.15.4 devices. The computer-executed method is provided on an IEEE 802.15.4 device, and causes a processor of the IEEE 802.15.4 device to perform steps that include determining the permission of backoff suspension and the intention of IEEE 802.15.4 device to perform backoff suspension, selecting the suspendable CSMA/CA control program if the backoff suspension is permitted and IEEE 802.15.4 device intends to perform backoff suspension. The suspendable CSMA/CA control program is configured to perform active CCA within each unit backoff period and suspend backoff if channel is detected to be busy, performing a CCA when backoff completes, transmitting frame when the detected channel status is an idle state or incrementing a number of backoff (NB) when the detected channel status is an busy state, determining if a NB exceeds the macMaxCSMABackoffs, incrementing a number of retransmissions (NR) when a NB exceeds the macMaxCSMABackoffs, and discarding frame when a NR exceeds macMaxFrameRetries.

Classes IPC  ?

• H04W 74/08 - Accès non planifié, p. ex. ALOHA

Abrégé

A system for sensing a state of a device is provided. The system includes an autoencoder comprising an encoder, a latent subnetwork, and an extended decoder. The encoder encodes each input data point of input data from an input state space into a latent space to produce latent data points and propagates the latent data points with a neural Ordinary Differential Equation (ODE) to estimate an initial point of latent dynamics of the device in the latent space. The latent subnetwork propagates the initial point till a time index of interest using the neural ODE to produce a state of latent dynamics of the device at the time index of interest. The extended decoder decodes the state of latent dynamics of the device into an output state space different from the input state space to produce output data including the state of the device at the time index of interest.

Classes IPC  ?

• G06N 3/0455 - Réseaux auto-encodeursRéseaux encodeurs-décodeurs
• G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions

Abrégé

A distance estimation method comprises transmitting a wave of radiation modulated in frequency domain by an emitter to a scene, receiving a reflection of the transmitted wave from the scene, and interfering a copy of the transmitted wave with the received reflection to generate a sequence of samples of the beat signal with wrapped phases in a time domain. The method also comprises estimating a frequency of the beat signal in the time domain in an iterative manner until a termination condition is met. The iterative estimation of the frequency of the beat signal is based on phase unwrapping of the samples of the beat signal subject to correlated phase error derived from phase noise statistics of the emitter and a linear regression fitting the frequency of the beat signal into the unwrapped phases of the beat signal.

Classes IPC  ?

• G01S 7/4911 - Émetteurs
• G01S 7/481 - Caractéristiques de structure, p. ex. agencements d'éléments optiques
• G01S 7/4915 - Mesure du temps de retard, p. ex. détails opérationnels pour les composants de pixelsMesure de la phase
• G01S 17/34 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement utilisant la transmission d'ondes continues, soit modulées en amplitude, en fréquence ou en phase, soit non modulées utilisant la transmission d'ondes continues modulées en fréquence, tout en faisant un hétérodynage du signal reçu, ou d’un signal dérivé, avec un signal généré localement, associé au signal transmis simultanément

Abrégé

A fault detection system is provided to extract fault signature from the time-domain stator current signal of a motor under varying load operations by solving a joint blind deconvolution-demodulation problem, where the stator current of a motor under varying operating conditions is modeled as a stator current of a steady operating condition influenced by the system response vector and a load modulation vector. A proximal alternating linearized minimization-type method is used to solve the joint blind deconvolution-demodulation problem, assuming that the spectrum of the sought-after signal is sparse. Motor fault detection is then performed using the recovered stator current of a steady operating condition.

Classes IPC  ?

• H02P 29/024 - Détection d’un défaut, p. ex. court circuit, rotor bloqué, circuit ouvert ou perte de charge
• G01R 31/34 - Tests de machines dynamoélectriques

Abrégé

The present disclosure provides a system and a method for jointly controlling one or multiple connected and automated vehicles (CAVs) and one or multiple human-driven vehicles (HDVs) subject to integer constraints for crossing each of multiple intersections on a road. The method comprises collecting digital representation of states of each of the CAVs, HDVs, and traffic signs, solving an optimization problem jointly optimizing traffic flows based on a macroscopic traffic flow model in a centralized traffic controller (CTC) subject to convex relaxation of the integer constraints, solving a multi-variable mixed-integer programming (MIP) problem in each of multiple intersection traffic controllers (ITCs) optimizing a cost function and minimizing tracking errors in traffic flow values of a microscopic traffic flow model with respect to relaxed traffic flow values from the CTC, and transmitting the optimized values of the control commands to the corresponding CAVs and corresponding traffic signs.

Classes IPC  ?

• G08G 1/09 - Dispositions pour donner des instructions variables pour le trafic
• G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
• G08G 1/081 - Commande des signaux de trafic plusieurs carrefours dépendant d'une commande commune

Abrégé

The present disclosure discloses a system and a method for controlling motion of an ego vehicle. The method includes collecting a feedback signal indicative of a current state of the ego vehicle and an environment, processing the feedback signal to determine a region of the state of the ego vehicle uplifted with admissible values of a control parameter, processing the feedback signal with a nominal controller to produce a nominal control command maintaining the state of the ego vehicle within the determined region, and evaluating a state function of an evasive controller with a value of the control parameter from the determined region to produce an evasive control command. The method further includes controlling the motion of the ego vehicle according to the nominal control command when the fault is not detected; and otherwise controlling the motion of the ego vehicle according to the evasive control command.

Classes IPC  ?

• B60W 50/035 - Mise des unités de commande dans un état prédéterminé, p. ex. en donnant la priorité à des éléments d'actionnement particuliers
• B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes

Abrégé

A camera is provided for reconstructing the surface of the object. The camera includes an optical module configured to spatially separate photons reflected from an object in a scene to form at least two focused and distinctly polarized images on a sensor, wherein the sensor is configured to receive the at least two polarized images on pixels the sensor and generate intensity values of the pixels, and a computing module including a processor and a memory having instructions stored thereon. According to the instructions, the processor computes depth values at points of a surface of the object based on a ratio of the intensity values of the pixels with respect to the at least two polarized images and reconstructs the surface of the object from the computed depth values.

Classes IPC  ?

• H04N 23/55 - Pièces optiques spécialement adaptées aux capteurs d'images électroniquesLeur montage
• G06T 7/521 - Récupération de la profondeur ou de la forme à partir de la télémétrie laser, p. ex. par interférométrieRécupération de la profondeur ou de la forme à partir de la projection de lumière structurée
• G06T 7/55 - Récupération de la profondeur ou de la forme à partir de plusieurs images
• H04N 23/95 - Systèmes de photographie numérique, p. ex. systèmes d'imagerie par champ lumineux

Abrégé

A tomographic imaging system is provided. The system receives measurements at frequencies of a wave-field scattered by an internal structure of an object, recursively reconstructs an image of the internal structure of the object until a termination condition is met, and renders the reconstructed image. For a current iteration, a frequency is added to previous frequencies used during a previous iteration to produce current frequencies, such that the added frequency is higher than frequencies present in the previous frequencies, and reconstructs a current image of the internal structure of the object that minimizes a difference between the scattered wave-field measured at the current frequencies and a wave-field synthetized from the current image. The wave-field synthesized from the current image is generated by a neural network operator. A previous image determined during the previous iteration initializes the reconstruction of the current image.

Classes IPC  ?

• G06T 7/00 - Analyse d'image

Abrégé

The present disclosure discloses a system and a method for controlling an operation of a vapor compression cycle based on a hybrid model of dynamics of the vapor compression cycle including a physics-based model and a data driven model. The method comprises executing a constrained Kalman smoother over the observed variables collected over multiple instances of time to jointly estimate the parameters of the physics-based model and states of the vapor compression cycle, and updating the data driven model to minimize a difference between the states estimated by executing the constrained Kalman smoother and the states predicted by the physics-based model. The method further comprises updating the hybrid model with the estimated parameters of the physics-based model and the updated data driven model, and controlling the operation of the vapor compression cycle using the updated hybrid model.

Classes IPC  ?

• F25B 49/02 - Disposition ou montage des dispositifs de commande ou de sécurité pour machines, installations ou systèmes du type à compression

Abrégé

The present disclosure provides a system and a method for controlling an operation of a manipulation system. The method comprises formulating an optimization problem based on a Stochastic Discrete-time Linear Complementarity Model (SDLCM) of a manipulation task, and a sample average approximation; solving the formulated optimization problem using an important-particle algorithm to compute an optimal state trajectory, an optimal feedforward control trajectory, an optimal complementarity variable trajectory, a state feedback gain, and a complementarity feedback gain; collecting, measurements indicative of a current state trajectory and a current complementarity variable trajectory; determining an online control input based on the optimal feedforward control trajectory, a deviation of the current state trajectory from the optimal state trajectory, a deviation of the current complementarity variable trajectory from the optimal complementarity variable trajectory, the state feedback gain, and the complementarity feedback gain; and controlling actuators of the manipulation system according to the online control input.

Classes IPC  ?

• B25J 9/16 - Commandes à programme

Abrégé

A network manager is provided for delivering a firmware/software program to multi-mode nodes and single-mode nodes arranged in a multi-hop wireless IoT network. The network manager includes a transceiver configured to perform wireless communication by transmitting the encoded packets of the firmware/software program to the first-hop nodes. The network manager divides firmware/software program into source blocks, encodes the source blocks into encoded blocks based on coding scheme, packs the encoded blocks into encoded packets, transmits the encoded packets to the first-hop nodes. In this case, the first-hop nodes are configured to receive, decode, re-encode and re-transmit the encoded packets to propagate firmware/software distribution to the other-hop nodes. The network manager keeps broadcasting the encoded packets to the first-hop nodes until a predetermined percent of the first-hop nodes receive the firmware/software program. In response to receiving a re-transmission request of missing source blocks of the firmware/software program from the first-hop nodes, the network manager re-broadcasts the missing source blocks.

Classes IPC  ?

• G06F 8/65 - Mises à jour
• H04L 67/00 - Dispositions ou protocoles de réseau pour la prise en charge de services ou d'applications réseau

Abrégé

Disclosed a method and system for identifying an existence, location and type of a weak-signal fault in an islanded inverter-based microgrid. The weak-signal fault includes a high impedance fault, an inverter DC-side short-circuit fault, and an inverter tripping fault, and usually fails to be detected by conventional relay methods due to small magnitude of fault current. Upon received voltage and current measurements from intelligent electronic devices installed in the microgrid, the variation mode decomposition algorithm is firstly applied to detect the existence of fault based on denoised time series of measurements using discrete wavelet transform algorithm. After detecting the presence of fault, the correlation-based matrix is applied to locate the suspicious fault locations, and then K-nearest neighbors model is utilized to identify the faulty branch among those locations using dynamic time warping algorithm to measure the distance between neighbors. Following fault localization, fault classification is done by observing sequence components and phasor measurements and feeding the observational inputs to a fault classification logic circuit model.

Classes IPC  ?

• H02H 7/22 - Circuits de protection de sécurité spécialement adaptés aux machines ou aux appareils électriques de types particuliers ou pour la protection sectionnelle de systèmes de câble ou de ligne, et effectuant une commutation automatique dans le cas d'un changement indésirable des conditions normales de travail pour appareillage de distribution, p. ex. système de barre omnibusCircuits de protection de sécurité spécialement adaptés aux machines ou aux appareils électriques de types particuliers ou pour la protection sectionnelle de systèmes de câble ou de ligne, et effectuant une commutation automatique dans le cas d'un changement indésirable des conditions normales de travail pour dispositifs de commutation
• H02H 1/00 - Détails de circuits de protection de sécurité

Abrégé

The present disclosure discloses a system and a method for controlling a system with mixed-state matter including a solid-state matter with parts forming a container including a volume of fluid. The method includes collecting a feedback signal indicative of a state of the system and determining a control command to an actuator of the system at a current control step by solving an optimal control problem changing the state of the system according to a control objective subject to a heterogenous model of dynamics of the system, including a model of dynamics of the solid-state matter mutually coupled with a model of dynamics of the volume of fluid in the container. The method further includes submitting the control command to the actuator of the system to change the state of the system.

Classes IPC  ?

• B64G 1/38 - Amortissement des oscillations, p. ex. amortisseurs de nutation
• G05D 1/08 - Commande de l'attitude, c. à d. élimination ou réduction des effets du roulis, du tangage ou des embardées

Abrégé

A vehicle controlled for traveling on a road having a geometric design defined by one or a combination of an alignment, a profile, and a cross-section of the road, such that different values of parameters of the geometric design of the road, traffic on the road, traffic rules for the flow of the traffic on the road define different traffic scenarios. The vehicle is controlled by transforming the mixed-integer non-convex constrained optimization problem for the current real-world traffic scenario into a mixed-integer convex optimization problem for an approximate representation of the real-world traffic scenario by relaxing the configuration parameters of the real-world scenarios and tightening corresponding limitation parameters. The transformed mixed-integer convex optimization problem for the approximate representation of the real-world traffic scenario is solved to produce a current control command for controlling one or multiple actuators of the vehicle.

Classes IPC  ?

• B60W 30/095 - Prévision du trajet ou de la probabilité de collision
• B60W 30/12 - Maintien de la trajectoire dans une voie de circulation
• B60W 30/14 - Régulateur d'allure
• B60W 50/00 - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier

Abrégé

The present disclosure provides a system and a method for controlling motion of a bank of elevators. The method includes accepting current requests for service by the bank of elevators, accepting a partial trajectory of a motion of a person moving in an environment serviced by the bank of elevators, and obtaining a probability of a future elevator request. The method further includes processing the partial trajectory with a neural network trained to estimate a weighted combination of probability density functions that indicates an arrival time distribution of the person, and generating a set of possible future requests jointly representing the probability of the future elevator request and the arrival time distribution. The method further includes optimizing a schedule of the bank of elevators to serve the current requests and the set of possible future requests, and controlling the bank of elevators according to the schedule.

Classes IPC  ?

• B66B 1/24 - Systèmes de commande à régulation, c.-à-d. avec action rétroactive, permettant d'agir sur la vitesse de déplacement, l'accélération ou la décélération
• B66B 1/28 - Systèmes de commande à régulation, c.-à-d. avec action rétroactive, permettant d'agir sur la vitesse de déplacement, l'accélération ou la décélération électriques

Abrégé

A system and method are provided for training neural network for controlling operation of system having non-linear dynamics represented by partial differential equations (PDEs). The method comprises collecting digital representation of time series data indicative of instances of function space of the system and measurements of state of the operation of the system. Collocation points corresponding to solutions of the PDE are generated. The neural network is trained using training data including the collected time series data and the collocation points to train parameters of non-linear operator. The neural network has autoencoder architecture including encoder to encode each instance of the training data into latent space, the non-linear operator to propagate the encoded instances into the latent space with transformation determined by parameters of the non-linear operator, and decoder to decode the transformed encoded instances of the training data to minimize a hybrid loss function.

Classes IPC  ?

• G05B 13/02 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
• G06N 3/0455 - Réseaux auto-encodeursRéseaux encodeurs-décodeurs
• G06N 3/08 - Méthodes d'apprentissage

Abrégé

A system and method for sound processing for performing multi-talker conversation analysis is provided. The sound processing system includes a deep neural network trained for processing audio segments of an audio mixture of the multi-talker conversation. The deep neural network includes a speaker-independent layer that produces a speaker-independent output, and a speaker-biased layer applied once independently to each of the audio segments for each multiple speakers of the audio mixture. The deep neural network also processes a time-invariant embedding by individually assigning each application of the speaker-biased layer to a corresponding speaker by inputting the corresponding time-invariant speaker embedding. The deep neural network thus produces data indicative of time-frequency activity regions of each speaker of the multiple speakers in the audio mixture from a combination of speaker-biased outputs.

Classes IPC  ?

• G10L 21/0272 - Séparation du signal de voix
• G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
• G10L 25/78 - Détection de la présence ou de l’absence de signaux de voix

Abrégé

A controller for controlling a robot is provided. The controller comprises a hierarchical multimodal reinforcement learning (RL) neural network including a first level controller and three second level controllers. The second level controllers comprise a first sub level controller to receive input data based on predefined questions, a second sub level controller to receive the input data by generating a validation question based on state of the RL neural network and a third sub level controller to determine the input data based on state of the RL neural network. The controller is configured to select one of the second level controllers using the first level controller to perform a first interaction relating to a task based on the state of the RL neural network; generate a control command using the selected second level controller based on the corresponding input data; and control operation of the robot by executing control command.

Classes IPC  ?

• B25J 9/16 - Commandes à programme
• B25J 13/00 - Commandes pour manipulateurs

Abrégé

A controller for controlling robotic manipulator according to a task is provided. The controller is to collect data relating to a state and an object property of an object, and execute a state adapter model to produce a state correction to state of the object having the object property different from a unitary property of a unitary object. The controller is to execute a control policy using the state correction to produce an action for the unitary object, and execute an action adapter model to produce an action correction to the action produced by the control policy. The state correction and action correction are produced based on difference between object property and unitary property. The control policy is to map a state of the unitary object to the action of the robotic manipulator to manipulate the unitary object according to the task.

Classes IPC  ?

• B25J 9/16 - Commandes à programme

Abrégé

The present disclosure provides a system and a method for estimating a future traffic density in an environment. The method comprises receiving, for at least one object in the environment, at least one partial trajectory and a sequence of observation vectors. The at least one object is represented by a plurality of particles. The method comprises processing the at least one partial trajectory with a trajectory prediction model to predict a location of each particle of the plurality of particles at a future time instant and processing the sequence of observation vectors with an entering particle prediction model to predict a probability of observing an entering particle at each ingress point at the future time instant. The future traffic density is estimated based on the predicted location of each particle and the predicted probability of observing the entering particle at each ingress point at the future time instant.

Classes IPC  ?

• G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
• G06T 7/20 - Analyse du mouvement

Abrégé

A distributed machine learning based traffic prediction method is provided for predicting traffic of roads. In this case, the distributed machine learning based traffic prediction method includes distributing global multi-task traffic models by a learning server to learning agents to locally train the traffic models, uploading locally trained traffic models by learning agents to the learning server, updating global multi-task traffic models by the learning server using locally trained traffic model parameters acquired from learning agents, generating a time-dependent global traffic map by the learning server using the well trained global multi-task traffic models, distributing the time-dependent global traffic map to vehicles traveling on the roads, and computing an optimal travel route with the least travel time by a vehicle using the time-dependent global traffic map based on a driving plan.

Classes IPC  ?

• G06N 3/098 - Apprentissage distribué, p. ex. apprentissage fédéré
• G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
• G08G 1/0967 - Systèmes impliquant la transmission d'informations pour les grands axes de circulation, p. ex. conditions météorologiques, limites de vitesse

Abrégé

A method, a system and a computer program product are provided for applying a neural network including an action sequence decoder for generating an action sequence for a robot to perform a task. The neural network is applied to generate the action sequence based on recordings demonstrating humans performing tasks. In an example, the method comprises collecting a recording and a sequence of captions describing scenes in the recording; extracting feature data from the recording; encoding the extracted feature data to produce a sequence of encoded features; and applying the action sequence decoder to produce a sequence of actions for the robot based on the sequence of encoded features having a semantic meaning corresponding to a semantic meaning of the sequence of captions. The feature data includes features of a video signal, an audio signal, and/or text transcription capturing a performance of the task.

Classes IPC  ?

• G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
• G10L 15/02 - Extraction de caractéristiques pour la reconnaissance de la paroleSélection d'unités de reconnaissance
• G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
• G10L 15/18 - Classement ou recherche de la parole utilisant une modélisation du langage naturel

Abrégé

The present disclosure discloses a system and a method for controlling an operation of a system subject to an uncertainty of an operation variable of the system. The method comprises collecting a number of samples of the uncertainty of the operation variable, constructing, based on the collected samples, an empirical quantile function associated with the uncertainty of the operation variable, determining confidence bounds on the empirical quantile function to bound an approximation error between the empirical quantile function and a true quantile function, determining an uncertainty set based on the empirical quantile function bounded by the confidence bounds, reformulating, based on the uncertainty set, a chance constraint into a deterministic constraint, solving an optimal control problem subject to the deterministic constraint to produce one or more control commands to one or more actuators of the system, and controlling the operation of the system based on the control commands.

Classes IPC  ?

• G05B 13/02 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques

Abrégé

A robotic controller controls orientation of an object in a desired orientation. The controller obtains pose data indicative of a location and an orientation of the object on a supporting surface and determines one or more control commands for actuating actuators, corresponding to the location and orientation of the object on the supporting surface. The actuators are activated according to the one or more control commands to apply impulse forces to the supporting surface with a likelihood of changing the orientation of the object to the desired orientation. The controller iteratively repeats these procedures until the object is oriented in the desired orientation.

Classes IPC  ?

• B25J 9/16 - Commandes à programme
• G05B 19/4155 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par le déroulement du programme, c.-à-d. le déroulement d'un programme de pièce ou le déroulement d'une fonction machine, p. ex. choix d'un programme

Abrégé

The present disclosure discloses a system and method for controlling motion of a vehicle. The method comprises collecting a signal indicative of objectives of the motion and a value of the disturbances, and minimizing an objective function subject to constraints defined by the objectives of the motion to produce optimized values of parameters of a sequence of splines. The method further comprises controlling the motion of the vehicle based on a model of differentially flat dynamics of the vehicle according to an optimal path defined by the optimized values of the parameters of the sequence of splines.

Classes IPC  ?

• G05D 1/10 - Commande de la position ou du cap dans les trois dimensions simultanément
• B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
• B64U 10/00 - Type de véhicule aérien sans pilote
• G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions

Abrégé

An anomaly detector for controlling a system is provided. The system comprises one or multiple tools to perform one or multiple tasks. The anomaly detector collects a feedforward signal indicative of a sequence of control inputs to the plurality of actuators and a feedback signal indicative of a sequence of outputs of the system caused by the plurality of actuators operated based on the sequence of control inputs. The anomaly detector further combines input state variables extracted from the feedforward signal and output state variables extracted from the feedback signal to form a sequence of extended states of the system. The attention model further encodes the sequence of extended states to produce an encoding of each extended state of the sequence of extended states in a latent space. The anomaly detector further detects an anomaly in a current operation of the system based on the encoded sequence of extended states.

Classes IPC  ?

• G05B 23/02 - Test ou contrôle électrique

Abrégé

A robotic controller is provided for generating sequences of movement primitives for sequential tasks of a robot having a manipulator. The controller includes at least one control processor, and a memory circuitry storing a dictionary including the movement primitives, a pretrained learning module, and a graph-search based planning module having instructions stored thereon. The controller to perform steps acquiring a planned task provided by an interface device operated by a user, wherein the planned task is represented by an initial state and a goal state with respect to an object, generating a planning graph by searching a feasible path of the object for the novel task using the graph-search based planning module and selecting movement primitives from the dictionary in the pretrained learning module, wherein the pretrained learning module has been trained based on demonstration tasks, parameterizing the feasible path represented by the movement primitives as dynamic movement primitives (DMPs) using the initial state and goal state, and implementing the parameterized feasible path as a trajectory according to the selected movement primitives using the manipulator of the robot by tracking and following the parameterized for the planned task.

Classes IPC  ?

• B25J 9/16 - Commandes à programme
• B25J 13/08 - Commandes pour manipulateurs au moyens de dispositifs sensibles, p. ex. à la vue ou au toucher

Abrégé

The present disclosure discloses a negative inductor device. The negative inductor device comprises a negative inductor comprising a ferromagnetic material and a conductive material arranged inside the ferromagnetic material. The negative inductor device further comprises a current limiting circuit electrically coupled to the negative inductor and configured to supply an electric current of magnitude within a range, the range being defined by a first local minimum and a second local minimum of a current-energy curve of the ferromagnetic material.

Classes IPC  ?

• H01F 38/02 - Adaptations de transformateurs ou d'inductances à des applications ou des fonctions spécifiques pour fonctionnement non linéaire
• H01F 7/06 - Électro-aimantsActionneurs comportant des électro-aimants
• H01F 17/04 - Inductances fixes du type pour signaux avec noyau magnétique

Abrégé

The present disclosure discloses a system and a method for controlling an operation of a robotic arm holding a tool for manipulating object. The method comprises collecting measurements of tactile sensors associated with the robotic arm, estimating, based on the collected measurements and constraints enforced by a Model Predictive Controller (MPC), a feedback signal indicative of a pose of the object, and executing the MPC configured to produce, based on the pose of the object, control commands for actuators of the robotic arm by optimizing a cost function minimizing a deviation of the pose of the object from a target pose of the object. The optimization of the cost function is subject to the constraints that constrain one or more forces acting on the object at one or more point of contacts to be within corresponding friction regions. The method further comprises controlling the actuators according to the control commands.

Classes IPC  ?

• B25J 9/16 - Commandes à programme
• B25J 13/08 - Commandes pour manipulateurs au moyens de dispositifs sensibles, p. ex. à la vue ou au toucher

Abrégé

The present disclosure provides an anomaly detector. The anomaly detector comprises an input interface configured to accept input data, a first neural network having an autoencoder architecture including an encoder trained to encode the input data and a decoder trained to decode the encoded input data to reconstruct the input data, and a loss estimator configured to compare a plurality of parts of the input data with corresponding plurality of parts of the reconstructed input data to determine a sequence of losses for different components of a reconstruction error. The anomaly detector further comprises a second neural network trained in a supervised manner to classify the sequence of losses to detect an anomaly to produce a result of anomaly detection including one or a combination of a type of the anomaly and a severity of the anomaly, and an output interface to render the result of anomaly detection.

Classes IPC  ?

• G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures

Abrégé

A system for magnetic refrigeration is provided. The system includes a layered structure formed by a sequence of a plurality of magnetocaloric material (MCM) components interlinked with a sequence of a plurality of Peltier modules. Each Peltier module of the plurality of Peltier modules is sandwiched between two MCM components of the plurality of MCM components. The system further includes a power source configured to concurrently power each Peltier module in the sequence of the plurality of Peltier modules. Current in each powered Peltier module flows in a constant direction. The system further includes a magnetic source configured to apply spatially uniform magnetic field to the sequence of the plurality of MCM components.

Classes IPC  ?

• F25B 21/02 - Machines, installations ou systèmes utilisant des effets électriques ou magnétiques utilisant l'effet PeltierMachines, installations ou systèmes utilisant des effets électriques ou magnétiques utilisant l'effet Nernst-Ettinghausen

Abrégé

The present disclosure discloses a controller and a method for controlling an electric motor. The controller comprises a feedback controller configured to generate a reference voltage vector, a hybrid flux observer configured to estimate a flux error vector based on a difference between a first stator flux linkage observed and a second stator flux linkage, and a position observer configured to estimate a position of a rotor of the electric motor based on a projection of the flux error vector in a direction orthogonal to a direction of a voltage error vector shifted with a phase of dynamics of the hybrid flux observer. The controller further comprises a state estimator configured to estimate a value of a state of operation of the electric motor based on the estimated position of the rotor, thereby closing a feedback control loop of the feedback controller.

Classes IPC  ?

• H02P 21/18 - Estimation de la position ou de la vitesse
• H02P 21/12 - Commande basée sur le flux statorique impliquant l’utilisation de détecteurs de position ou de vitesse du rotor
• H02P 21/14 - Estimation ou adaptation des paramètres des machines, p. ex. flux, courant ou tension
• H02P 21/20 - Estimation du couple

Abrégé

There is provided an audio processing system and method comprising an input interface that receives an input audio mixture and transforms it into a time-frequency representation defined by values of time-frequency bins, a processor that maps the values of time-frequency bins into a hyperbolic space by executing an embedding neural network trained to associate each time-frequency bin to a high-dimensional embedding and projecting each high-dimensional embedding into the hyperbolic space, and an output interface that accepts a selection of at least a portion of the hyperbolic space and renders selected hyperbolic embeddings falling within the selected portion of the hyperbolic space.

Classes IPC  ?

• G10L 21/0308 - Séparation du signal de voix caractérisée par le type de mesure du paramètre, p. ex. techniques de corrélation, techniques de passage par zéro ou techniques prédictives
• G01H 3/08 - Analyse des fréquences présentes dans des vibrations complexes, p. ex. en comparant les harmoniques présentes
• G10L 25/18 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par le type de paramètres extraits les paramètres extraits étant l’information spectrale de chaque sous-bande
• G10L 25/21 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par le type de paramètres extraits les paramètres extraits étant l’information sur la puissance
• G10L 25/30 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par la technique d’analyse utilisant des réseaux neuronaux
• G10L 25/51 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes spécialement adaptées pour un usage particulier pour comparaison ou différentiation

Abrégé

Embodiments of the present disclosure disclose a method and a system for video anomaly detection. The system is configured to collect a sequence of input video frames of an input video of a scene. In addition, the system is configured to partition each input video frame of the sequence of input video frames into a plurality of input video patches. Further, the system is configured to process each of the plurality of input video patches with one or more classifiers. Each of the one or more classifiers corresponds to a deep neural network trained to estimate one or more attributes of the plurality of input video patches from an output of a penultimate layer of the deep neural network. Furthermore, the system is configured to compare the output of the penultimate layer. The system is further configured to detect an anomaly based on the output of the penultimate layer.

Classes IPC  ?

• G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
• G06V 10/62 - Extraction de caractéristiques d’images ou de vidéos relative à une dimension temporelle, p. ex. extraction de caractéristiques axées sur le tempsSuivi de modèle
• G06V 10/74 - Appariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques
• G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• G06V 20/52 - Activités de surveillance ou de suivi, p. ex. pour la reconnaissance d’objets suspects

Abrégé

The present disclosure provides a system and a method for controlling a vapor compression system (VCS). The method comprises collecting data points indicative of control of the operation of the VCS with different combinations of setpoints for different actuators of the VCS and corresponding costs of operation of the VCS for each of the different combinations of setpoints, and computing, using a Local Search Region Bayesian optimization (LSR-BO) of the combinations of setpoints and their corresponding costs of operation, a probabilistic surrogate model. The probabilistic surrogate model defines at least first two order moments of the cost of operation. The method further comprises selecting from the probabilistic surrogate model a current combination of setpoints improving the cost of operation with respect to a previous combination of setpoints, according to an acquisition function of the first two order moments of the cost of operation subject to a LRS constraint.

Classes IPC  ?

• F24F 11/47 - Réaction aux coûts énergétiques
• F24F 11/64 - Traitement électronique utilisant des données mémorisées au préalable
• F25B 49/02 - Disposition ou montage des dispositifs de commande ou de sécurité pour machines, installations ou systèmes du type à compression
• G05B 19/042 - Commande à programme autre que la commande numérique, c.-à-d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques

Abrégé

A fault detection system of extracting fault signature of a motor operating at varying speed or varying load conditions is provided. The fault detection system includes a sensor interface configured to acquire sensor signals from sensors arranged at predetermined positions of the induction machine, wherein the sensor signals are indicative of an eccentricity level of a rotor of the induction machine, a memory coupled with a processor. The instructions include steps a sensor interface configured to acquire operation signals of the induction machine; a memory configured to store a computer-implemented fault detection method by extracting fault signals in the frequency domain from the frequency spectrum formed by a minimum variance beam-forming method.

Classes IPC  ?

• G01R 31/34 - Tests de machines dynamoélectriques
• G01M 13/028 - Analyse acoustique ou des vibrations

Abrégé

An abnormality diagnosis device includes: a first interface to obtain a value of a driving current for driving a motor; and a processor to access a database including calculation data to be used to calculate a degree of abnormality of the motor, wherein the processor extracts a feature quantity for calculating the degree of abnormality from a current waveform specified by a value of the driving current, and calculates the degree of abnormality of the motor based on the extracted feature quantity and the calculation data.

Classes IPC  ?

• H02P 21/22 - Commande du courant, p. ex. en utilisant une boucle de commande
• H02P 29/028 - Détection d’un défaut, p. ex. court circuit, rotor bloqué, circuit ouvert ou perte de charge le moteur continuant de fonctionner malgré le défaut, p. ex. élimination, compensation ou résolution du défaut

Abrégé

An audio processing system and method for processing audio is disclosed. The audio processing system collects an input audio signal indicative of degraded measurements of a target audio waveform. The input audio signal is restored with recursive restoration that recursively restores the input audio signal until a termination condition is met. A current iteration of the recursive restoration applies a restoration operator configured to restore a degraded audio signal conditioned on a current level of severity of degradation and degrades the degraded audio signal deterministically with a level of severity less than the current level of severity. A target signal estimate indicative of enhanced measurements of the audio waveform is generated as output.

Classes IPC  ?

• G10L 21/0308 - Séparation du signal de voix caractérisée par le type de mesure du paramètre, p. ex. techniques de corrélation, techniques de passage par zéro ou techniques prédictives
• G10L 25/30 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par la technique d’analyse utilisant des réseaux neuronaux

Abrégé

The present disclosure discloses a semiconductor device comprising a plurality of epitaxial layers including a barrier layer and a channel layer such that two-dimensional carrier densities are formed at an interface of the barrier layer and the channel layer, wherein a priority of charge carriers of the channel layer is based on a polarization direction of the barrier layer, and wherein the polarization direction of the barrier layer can be changed by applying an electric field across the barrier layer. The semiconductor device further comprises a first source terminal and a second source terminal, wherein in one of the first source terminal and the second source terminal is ohmic to electrons and other one is ohmic to holes. The semiconductor device further comprises a first drain terminal and a second drain terminal, a gate terminal, and a set terminal ohmic to the channel layer.

Classes IPC  ?

• H01L 29/778 - Transistors à effet de champ avec un canal à gaz de porteurs de charge à deux dimensions, p.ex. transistors à effet de champ à haute mobilité électronique HEMT
• H01L 29/20 - Corps semi-conducteurs caractérisés par les matériaux dont ils sont constitués comprenant, à part les matériaux de dopage ou autres impuretés, uniquement des composés AIIIBV
• H01L 29/205 - Corps semi-conducteurs caractérisés par les matériaux dont ils sont constitués comprenant, à part les matériaux de dopage ou autres impuretés, uniquement des composés AIIIBV comprenant plusieurs composés dans différentes régions semi-conductrices
• H01L 29/417 - Electrodes caractérisées par leur forme, leurs dimensions relatives ou leur disposition relative transportant le courant à redresser, à amplifier ou à commuter
• H01L 29/45 - Electrodes à contact ohmique
• H01L 29/47 - Electrodes à barrière de Schottky

Abrégé

A system for performing end-to-end automatic speech recognition (ASR). The system configured to collect a sequence of acoustic frames associated with a mixture of speeches performed by multiple speakers. Each frame from the sequence of acoustic frames is encoded using a multi-head encoder which encodes each frame into a likelihood of a transcription output and a likelihood of an identity of a speaker. The multi-head encoder thus produces a sequence of likelihoods of transcription outputs and a sequence of likelihoods of identities of the speakers corresponding to the sequence of acoustic frames that are decoded using a decoder performing an alignment operation for producing a sequence of transcription outputs annotated with identities of the speakers, for performing speaker separation.

Classes IPC  ?

• G10L 17/06 - Techniques de prise de décisionStratégies d’alignement de motifs
• G06F 40/169 - Annotation, p. ex. données de commentaires ou notes de bas de page
• G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
• G10L 15/26 - Systèmes de synthèse de texte à partir de la parole

Abrégé

Embodiments of the present disclosure provide a method of training a neural network model for controlling an operation of a system represented by partial differential equations (PDEs). The method comprises collecting digital representation of time series data indicative of measurements of the operation of the system at different instances of time. The method further comprises training the neural network model having an autoencoder architecture including an encoder to encode the digital representation into a latent space, a linear predictor to propagate the digital representation into the latent space, and a decoder to decode the digital representation to minimize a loss function including a prediction error between outputs of the neural network model decoding measurements of the operation at an instant of time and measurements of the operation collected at a subsequent instance of time, and a residual factor of the PDE having eigenvalues dependent on parameters of the linear predictor.

Classes IPC  ?

• G06N 3/08 - Méthodes d'apprentissage
• G06N 3/0455 - Réseaux auto-encodeursRéseaux encodeurs-décodeurs

Abrégé

The present disclosure discloses a system and a method for controlling a permanent magnet synchronous motor to optimally track a reference torque. The method comprises reformulating a model of the permanent magnet synchronous motor based on one or more unknown parameters of the model, and the reference torque, determining an initial feedback control policy and an initial feedforward control policy, based on priori knowledge of parameters of the reformulated model of the permanent magnet synchronous motor, and executing iteratively a gain tuning algorithm, until a termination condition is met, to determine an optimal feedback gain and an optimal feedforward gain. The method further comprises determining a control command based on the optimal feedback gain and the optimal feedforward gain, and controlling the permanent magnet synchronous motor based on the determined control command to optimally track the reference torque.

Classes IPC  ?

• H02P 25/022 - Moteurs synchrones
• H02P 6/08 - Dispositions pour commander la vitesse ou le couple d'un seul moteur
• H02P 6/34 - Modèle ou simulation pour la commande
• H02P 21/14 - Estimation ou adaptation des paramètres des machines, p. ex. flux, courant ou tension

Abrégé

A fault detection system of eccentricity severity of an induction machine including a rotor and stator is provided. The fault detection system includes a sensor interface configured to acquire sensor signals from sensors arranged at predetermined positions of the induction machine, wherein the sensor signals are indicative of an eccentricity level of a rotor of the induction machine, a memory coupled with a processor. The memory stores training data sets and instructions implementing a learning-based fault detection method for the induction machine. The instructions include steps of generating an eccentricity feature matrix from the sensor signals, where in the sensor signals include load torque, rotor speed, vibration acceleration of the rotor, vibration speed of the rotor, and current spectral of the stator or the induction machine, determining an eccentricity level of the induction machine based on the eccentricity feature matrix using the learning-based fault detection method, wherein the learning-based fault detection method is configured to find the eccentricity level from learning-based eccentricity feature matrix data sets.

Classes IPC  ?

• G01R 31/34 - Tests de machines dynamoélectriques
• H02P 29/024 - Détection d’un défaut, p. ex. court circuit, rotor bloqué, circuit ouvert ou perte de charge

Abrégé

A system and method for motor eccentricity fault detection is disclosed. The method includes extraction of fault-related features through topological data analysis (TDA) for motor current signals and apply them to motor eccentricity fault detection. The method further includes the procedure of obtaining topological features from time-domain data and representing them in persistence diagrams and vectorized Betti sequences. The method further includes the extraction of fault-related features from the obtained topological features of the data, which can be distinctively associated with not only fault type but also fault severity level. Further, the method includes use of machine learning models to extract fault-related features from TDA, for the prediction of motor eccentricity fault level, even for data from new eccentricity levels that are not seen in the training data.

Classes IPC  ?

• G05B 23/02 - Test ou contrôle électrique

Abrégé

The present disclosure discloses a system and a method for controlling an operation of a machine according to a task. The method comprises formulating an original quadratic program (QP) for optimizing an objective function subject to equality constraints and inequality constraints, lifting the equality constraints and the inequality constraints into a lifted space by a lifting operation introducing an additional non-negative variable, and transforming the objective function of the original QP into a quadratic objective function. The quadratic objective function subject to the lifted equality and inequality constraints forms a homogeneous QP in the lifted space. The method further comprises solving the homogeneous QP to produce a solution in the lifted space and controlling the machine according to an infeasibility protocol when a value of the additional non-negative variable in the solution in the lifted space equals zero.

Classes IPC  ?

• G05B 19/4155 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par le déroulement du programme, c.-à-d. le déroulement d'un programme de pièce ou le déroulement d'une fonction machine, p. ex. choix d'un programme

Abrégé

A system for controlling an operation of an air-conditioning system including a heat exchanger is provided. The system comprises a processor that executes a neural network trained to simulate an operation of the heat exchanger for a test control input, to produce an output of the simulation based on historical data defining a state of the heat exchanger. The historical data includes a sequence of historical control inputs provided to the heat exchanger and a sequence of historical outputs of the operation of the heat exchanger corresponding to the sequence of historical control inputs. The processor determines a control command to the air-conditioning system based on the predicted test output of the simulation of the operation of the heat exchanger for the test control input and transmits the determined control command to an actuator of the air-conditioning system.

Classes IPC  ?

• G05B 13/04 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques impliquant l'usage de modèles ou de simulateurs
• F24F 11/64 - Traitement électronique utilisant des données mémorisées au préalable
• F24F 11/81 - Systèmes de commande caractérisés par leurs grandeurs de sortieDétails de construction de tels systèmes pour la commande de la température de l’air fourni en commandant l’apport en air aux échangeurs de chaleur ou aux canaux de dérivation
• G05B 13/02 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques

Abrégé

An optical coherence tomography (OCT) system comprises an interferometer configured to split incident light into a reference beam and a test beam, and to interfere the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern. The OCT system also comprises a spectrometer configured to analyze spectral components of the interference pattern at non-uniformly sampled wavenumbers. A computer-readable memory of the OCT system is configured to store a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers. The OCT system further comprises a processor configured to determine the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of the measured intensities with the measurement model.

Classes IPC  ?

• A61B 5/00 - Mesure servant à établir un diagnostic Identification des individus
• G01B 9/02091 - Interféromètres tomographiques, p. ex. à cohérence optique

Abrégé

A control system collects a graph-based representation of the power distribution system as a radial tree of nodes connected by edges. Each node represents a section of the power distribution system isolated by switches and each edge represents a switch that connects a section represented by the node with a neighboring section represented by the neighboring node. Each node has a property of power demand of a corresponding section governed by a difference between demanded and available energy for the section, and each edge has a property constraining throughput of energy through the switch in a direction of a power flow. The control system solves an optimization problem to determine the states of the edges and controls the switches based on the optimized states of the corresponding edges.

Classes IPC  ?

• H02J 3/46 - Dispositions pour l’alimentation en parallèle d’un seul réseau, par plusieurs générateurs, convertisseurs ou transformateurs contrôlant la répartition de puissance entre les générateurs, convertisseurs ou transformateurs

Abrégé

A controller for controlling an operation of a robot to execute a task is provided. The controller comprises a memory configured to store a set of dynamic movement primitives (DMPs) associated with the task. The set of DMPs comprise a set of at least two dynamical systems: a function representing point attractor dynamics and a forcing function corresponding to a learned demonstration of the task. The controller comprises a processor configured to transform the set of DMPs to a set of constrained DMPs (CDMPs) by determining a perturbation function associated with the forcing function. The perturbation function is associated with a set of operational constraints. The processor is further configured to solve, a non-linear optimization problem for the set of CDMPs based on the set of operational constraints and generate, a control input for controlling the robot for executing the task, based on the solution.

Classes IPC  ?

• B25J 9/16 - Commandes à programme

Abrégé

Embodiments of the present disclosure provide a wire electric discharge machine (EDM) including a delivery system with one or combination of a wire electrode and a workpiece for delivering the wire electrode and the workpiece into proximity of each other and an energy source for creating electric discharge between the wire electrode and the workpiece. The wire EDM includes a wire electrode position measurement unit including light source to illuminate the wire electrode with encoded illumination pattern and a camera for acquiring a set of images of the wire electrode illuminated by the encoded illumination pattern. The wire EDM includes a processor to reconstruct positions of a segment of the wire electrode at a reconstruction rate greater than an acquisition rate of the camera by utilization of compressive sensing with sparse reconstruction technique and a controller to control the delivery system and the energy source based on the reconstructed positions.

Classes IPC  ?

• B23H 7/20 - Circuits électriques spécialement adaptés à cet effet, p. ex. alimentation pour commande de programme, p. ex. commande adaptative
• B23H 7/10 - Support, enroulage ou connexion électrique du fil-électrode
• G06T 5/00 - Amélioration ou restauration d'image
• G06T 5/50 - Amélioration ou restauration d'image utilisant plusieurs images, p. ex. moyenne ou soustraction
• G06V 10/145 - Éclairage spécialement adapté à la reconnaissance de formes, p. ex. utilisant des réseaux

Abrégé

Embodiments of the present disclosure disclose a method and a system for tracking the position of the one or more moving objects. The method includes collecting GNSS measurement data of satellite signals transmitted from multiple satellites. The method further includes extracting values of a plurality of features from the GNSS measurement data. The method includes mapping the extracted values of the plurality of features to a source domain. The method includes classifying the mapped transformed plurality of features using a neural network. The neural network is trained over simulated data sampled from a source domain. The method includes identifying multipath measurements of the GNSS measurement data based on classification of the corresponding mapped transformed plurality of features. The method includes tracking the position of the one or more moving objects by processing identification of GNSS measurement data affected by multipath.

Classes IPC  ?

• G01S 19/22 - Problèmes liés aux multitrajets
• G01S 19/37 - Détails de matériel ou de logiciel de la chaîne de traitement des signaux
• G06N 3/08 - Méthodes d'apprentissage

Abrégé

The present disclosure provides a multiple-input multiple-output (MIMO) radar system and a method for detecting an object in a scene. The method comprises transmitting frequency modulated continuous wave (FMCW) in a radio frequency (RF) band, and collecting radar measurements of the scene sampled in a time-frequency domain within an intermediate frequency (IF) bandwidth. The method further comprises transforming the radar measurements into range-doppler space to produce measurements of different segments of the scene for different range-doppler bins formed by intersections of different range bins with different Doppler bins, classifying a presence of the hypothetical transmitter at different segments of the scene according to a signal model with an internal classification, combining the results of the classification to produce parameters of the object, and outputting the parameters of the object.

Classes IPC  ?

• G01S 13/58 - Systèmes de détermination de la vitesse ou de la trajectoireSystèmes de détermination du sens d'un mouvement
• G01S 13/931 - Radar ou systèmes analogues, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres

Abrégé

The present disclosure provides a feedback controller and method for controlling an operation of a device at different control steps. The feedback controller comprises at least one processor, and the memory having instructions stored thereon that, when executed by the at least one processor, causes the feedback controller, for a control step, to collect a measurement indicative of a state of the device at the control step, and execute, recursively until a termination condition is met, a probabilistic solver parameterized on a control input to an actuator operating the device to produce a control input for the control step. The feedback controller is further configured to control the actuator operating the device based on the produced control input.

Classes IPC  ?

• G05B 13/04 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques impliquant l'usage de modèles ou de simulateurs
• G05B 6/02 - Dispositions de rétroaction interne pour obtenir des caractéristiques particulières, p. ex. proportionnelles, intégrales ou différentielles électriques

Abrégé

A controller for controlling an entity is provided. The controller comprises a memory to store a hierarchical multimodal reinforcement learning (RL) neural network, and a processor. The hierarchical multimodal RL neural network includes a first level controller and two second level controllers. Each of the second level controllers comprise a first sub level controller relating to a first modality and a second sub level controller relating to a second modality. The first modality is different from the second modality. The processor is configured to select one of the two second level controllers to perform a first sub-task relating to a task, using the first level controller, based on input data and a state of the hierarchical multimodal RL neural network. The selected second level controller is configured to determine a set of control actions to perform the first sub-task, and control the entity based on the set of control actions.

Classes IPC  ?

• G05B 13/02 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
• G10L 15/06 - Création de gabarits de référenceEntraînement des systèmes de reconnaissance de la parole, p. ex. adaptation aux caractéristiques de la voix du locuteur
• G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
• G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine

Abrégé

A control system for controlling movement of a vehicle, is disclosed. The control system is configured to construct a graph having multiple nodes defining states of the vehicle. The multiple nodes comprise an initial node defining initial state and a target node defining target state. Each pair of nodes is connected by an edge defined by collision-free motion primitives where the nodes comprise motion cusps. Multiple nodes connected through edges form a first path. A first number of motion cusps in the first path is determined and the graph is expanded to add new nodes until a termination condition is met on determining that the first number of motion cusps is above a threshold. The expansion of the graph is subjected to a constraint associated with a total number of motion cusps. Further a second path is determined having lesser motion cusps than the first path.

Classes IPC  ?

• B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
• B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
• B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant
• B60W 30/095 - Prévision du trajet ou de la probabilité de collision

Abrégé

A system and method for reverberation reduction is disclosed. A first Deep Neural Network (DNN) produces a first estimate of a target direct-path signal from a mixture of acoustic signals that include the target direct-path signal and a reverberation of the target direct-path signal. A filter modeling a room impulse response (RIR) for the first estimate is estimated. The filter when applied to the first estimate of the target direct-path signal generates a result closest to a residual between the mixture of the acoustic signals and the first estimate of the target direct-path signal according to a distance function. The estimated filter is used for modeling the RIR.

Classes IPC  ?

• G10L 21/0232 - Traitement dans le domaine fréquentiel
• G10L 15/06 - Création de gabarits de référenceEntraînement des systèmes de reconnaissance de la parole, p. ex. adaptation aux caractéristiques de la voix du locuteur
• G10L 25/30 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par la technique d’analyse utilisant des réseaux neuronaux
• G10L 21/0224 - Traitement dans le domaine temporel

Abrégé

An artificial intelligence (AI) low-latency processing system is provided. The low-latency processing system includes a processor; and a memory having instructions stored thereon. The low-latency processing system is configured to collect a sequence of frames jointly including information dispersed among at least some frames in the sequence of frames, execute a timing neural network trained to identify an early subsequence of frames in the sequence of frames including at least a portion of the information indicative of the information, and execute a decoding neural network trained to decode the information from the portion of the information in the subsequence of frames, wherein the timing neural network is jointly trained with the decoding neural network to iteratively identify the smallest number of subframes from the beginning of a training sequence of frames containing a portion of training information sufficient to decode the training information.

Classes IPC  ?

• G06N 3/08 - Méthodes d'apprentissage
• G06N 3/04 - Architecture, p. ex. topologie d'interconnexion
• H04N 19/172 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c.-à-d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant une zone de l'image, p. ex. un objet la zone étant une image, une trame ou un champ

Abrégé

The present disclosure provides a method and a system for training a neural network suitable for localization of a device within an environment based on signals received by the device. The method comprises training a bi-regressor neural network to identify locations from labeled data, wherein the bi-regressor neural network includes a feature extractor and a bi-regressor including two regressors; training parameters of the bi-regressor using the labeled data and unlabeled data, such that each of the two regressors identifies the same labeled locations while processing the labeled data and identifies different locations while processing the unlabeled data; and training parameters of the feature extractor using an adversarial discriminator to extract domain invariant features from the unlabeled data with statistical properties of the labeled data according to the adversarial discriminator such that each of the two regressors identifies the same locations while processing the domain invariant features.

Classes IPC  ?

• G06N 3/094 - Apprentissage antagoniste
• G06F 18/213 - Extraction de caractéristiques, p. ex. en transformant l'espace des caractéristiquesSynthétisationsMappages, p. ex. procédés de sous-espace
• G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
• G06F 18/25 - Techniques de fusion

Abrégé

A device for controlling an operation of a system performing a task determines a current control input based on the feedback signal by solving a polynomial optimization of a polynomial function with a reformulation derived by introducing additional variables reducing the degree of the polynomial function till a target degree subject to constraints on a structure of the additional variables. The device solves a mixed-integer optimization problem to find a subset of encodings among all possible encodings of factorizations of the polynomial function that reduce the degree of the polynomial function to the target degree with a predetermined minimum number of additional variables and selects an optimal encoding from the subset of encodings with an optimal relaxation bound.

Classes IPC  ?

• G05B 6/02 - Dispositions de rétroaction interne pour obtenir des caractéristiques particulières, p. ex. proportionnelles, intégrales ou différentielles électriques

Abrégé

A cross-modality knowledge transfer system is provided for adapting one or more source model networks to one or more target model networks. The system is configured to perform steps of providing the TI paired datasets through the source feature encoders of the one or more source model networks, extracting TI source features and TI source moments from the TI paired data by the BN layers of the one or more source model networks, providing the TI paired datasets and the unlabeled TR datasets through the one or more target model networks to extract TI target features and TR target moments, training jointly all the feature encoders of the one or more target model networks by matching the extracted TI target features and TR target moments with the TI source features and TI source moments along with mixing weights, and forming a final target model network by combining the trained one or more target model networks.

Classes IPC  ?

• G06N 3/096 - Apprentissage par transfert
• G06V 10/74 - Appariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques
• G06V 10/77 - Traitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux

Abrégé

A system jointly estimates states of GNSS receivers moving in a region using measurements of a Global Navigation Satellite System (GNSS). The system clusters the GNSS receivers into different clusters subject to a constraint on an upper bound on each cluster and executes a set of probabilistic filters corresponding to the set of clusters to estimate the states of GNSS receivers in each cluster. Each probabilistic filter estimates the states of the GNSS receivers in a corresponding cluster by fusing the GNSS data collected from the GNSS receivers in the cluster to jointly reduce an estimation error of each of the GNSS receivers in the cluster. The DES updates the cluster assignments based on a measure of estimation error in the states of different GNSS receivers in different clusters.

Classes IPC  ?

• G01S 19/51 - Positionnement relatif
• G01S 19/39 - Détermination d'une solution de navigation au moyen des signaux émis par un système de positionnement satellitaire à radiophares le système de positionnement satellitaire à radiophares transmettant des messages horodatés, p. ex. GPS [Système de positionnement global], GLONASS [Système mondial de satellites de navigation] ou GALILEO

Abrégé

A system and a method for detecting anomalous sound are disclosed. The method includes receiving an audio signal from a sound source in a recording environment. The sound source and the recording environment are characterized by a set of attributes including a first attribute pertaining to a first attribute type and a second attribute pertaining to a second attribute type. A multi-head neural network is trained to extract from the received audio signal a first embedding vector indicative of the first attribute type and a second embedding vector indicative of the second attribute type. The first embedding vector is compared with a first set of embedding vectors to classify attributes of the first attribute type and the second embedding vector is compared with a second set of embedding vectors to classify attributes of the second attribute type, to determine a result of anomaly detection.

Classes IPC  ?

• G01H 3/08 - Analyse des fréquences présentes dans des vibrations complexes, p. ex. en comparant les harmoniques présentes
• G01H 1/00 - Mesure des vibrations dans des solides en utilisant la conduction directe au détecteur
• G06N 3/0464 - Réseaux convolutifs [CNN, ConvNet]

Abrégé

The present disclosure discloses a system and a method for controlling a device using a compound probabilistic filter. The method comprises collecting a sequence of measurements indicative of the state of the device at different control steps. Further, the method comprises executing iteratively a compound probabilistic filter configured to track the state of the device at each of the different control steps using the sequence of measurements to produce a sequence of states of the device corresponding to the sequence of measurements. Furthermore, the method comprises controlling the device using the tracked state of the device.

Classes IPC  ?

• G01S 19/39 - Détermination d'une solution de navigation au moyen des signaux émis par un système de positionnement satellitaire à radiophares le système de positionnement satellitaire à radiophares transmettant des messages horodatés, p. ex. GPS [Système de positionnement global], GLONASS [Système mondial de satellites de navigation] ou GALILEO
• G01S 19/37 - Détails de matériel ou de logiciel de la chaîne de traitement des signaux
• G01S 19/22 - Problèmes liés aux multitrajets
• B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes

Abrégé

A method and system for blockchain based monitoring and management of industrial automation systems are provided. The industrial automation systems comprise a blockchain-based common runtime for programmable logic controllers (PLCs) used in the industrial automation systems, in the form of a blockchain-integrated unikernel for PLCs. The unikernel is configured to provide functionalities related to security checks available in blockchain technology, an immutable audit trail of the operations within the industrial automation system, trusted, remote updates of industrial firmware by authenticating the updates through the blockchain, and automated integrity checks of controller functionality by comparing against the blockchain, among others.

Classes IPC  ?

• H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
• H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
• G05B 19/05 - Automates à logique programmables, p. ex. simulant les interconnexions logiques de signaux d'après des diagrammes en échelle ou des organigrammes

Abrégé

A system and method for automated construction of a stochastic deep neural network (DNN) architecture is provided. The framework of invention automatically searches for most relevant stochastic modes underlaying datasets for variational Bayesian inference. The invention provides a way to use heterogenous, irregular, and mismatched beliefs in stochastic sampling for intermediate representation in DNNs with a capability of an automatically tuning mechanism of posterior, prior, and likelihood models to enable accurate generative models and uncertainty models for machine learning tasks. The system further allows adjustable discrepancy measure to regularize intermediate representation by variants of divergence metrics including Renyi's alpha, beta, and gamma divergences. The invention enables diverse mixture combinations of stochastic models for misspecified and unspecified probabilistic relations in an automatic fashion. Accordingly, the representation capability of variational autoencoders, variational information bottlenecks, denoising diffusion probabilistic models and other stochastic DNNs are improved.

Classes IPC  ?

• G06N 3/04 - Architecture, p. ex. topologie d'interconnexion

Abrégé

A system and a computer-implemented method using physics-informed neural network (PINN) are provided for data communications. At a transmitter, the method is configured to acquire source data to be transmitted, encode the source data to codewords based on forward error correction (FEC) codes, map the codewords to amplitude symbols, modify the mapped amplitude symbols to pre-equalized symbols including pre-distort channel impairments symbols based on a predetermined physical model, and transmit digital data of the pre-equalized symbols over a channel as channel data. At a receiver, the method is configured to receive and demodulate the channel data from the channel to produce an initial estimate of bits of the received channel data, mitigate channel noise and waveform distortions in the channel data based on the initial estimate, convert the channel data consisting of shaped non-uniform symbols into a deshaped bit sequence as a uniform data sequence, decode the deshaped bit sequence to correct residual errors in the converted channel data, and store the corrected channel data to a data sink.

Classes IPC  ?

• G06N 3/045 - Combinaisons de réseaux
• G06N 3/08 - Méthodes d'apprentissage

Abrégé

A computer-implemented method is provided for training multi RL agent networks generating device parameters of circuits. The method includes acquiring inputs with respect to a desired circuit specification of a circuit, a device parameter, a topology of the circuit, a final state corresponding to a maximum step, wherein the desired circuit specification includes a gain, bandwidth, phase margin, power consumption, output power and power efficiency, wherein each of the RL agent networks is configured to perform transmitting an action selected from a set of actions to an environment module, updating the device parameters of the circuit with respect to a circuit specification, obtaining a current specification of the circuit by simulating a netlist of the circuit based on the updated device parameters using a circuit simulator of the environment module, wherein the environment module includes the netlist of the circuit, acquiring a reward from the environment module, wherein the reward is computed based on a difference between the current specification and the desired specification, wherein the steps of the transmitting, updating, obtaining and acquiring are continued until the reward reaches to a threshold value or a number of steps reach a preset value, and generating the satisfied updated device parameters via the interface.

Classes IPC  ?

• G06F 30/27 - Optimisation, vérification ou simulation de l’objet conçu utilisant l’apprentissage automatique, p. ex. l’intelligence artificielle, les réseaux neuronaux, les machines à support de vecteur [MSV] ou l’apprentissage d’un modèle
• G06F 30/3308 - Vérification de la conception, p. ex. simulation fonctionnelle ou vérification du modèle par simulation

Abrégé

The present disclosure provides a controller for controlling an ego vehicle in an uncertain environment. The controller is caused to acquire knowledge of the environment from measurements associated with sensors the ego. The measurements are based on a state of the ego vehicle and sensing instructions associated with controlling an operation of the sensors. The controller is further caused to estimate a state of the environment, including uncertainty of a state of the at least one moving object or obstacle in the environment. Further a sequence of control inputs is determined by solving a multivariable and a multistage stochastic constrained optimization of a model of the motion of the ego vehicle. The controller is then caused to control the ego vehicle and the sensors based on the sequence of control inputs and the sequence of sensing instructions.

Classes IPC  ?

• B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant
• B60W 50/00 - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier
• B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes

Abrégé

A computer-implemented method for maintaining a spacecraft near an orbit comprises steps of detecting that a distance from the spacecraft to the orbit is greater than a spacecraft threshold and in response, linearizing dynamics of the spacecraft from a current time over a time horizon with respect to a high-fidelity reference trajectory to produce a state transition matrix (STM) for an uncontrolled motion of the spacecraft within the time horizon. The STM includes non-expanding eigenvectors with magnitudes less than or equal to one and expanding eigenvectors with magnitudes greater than one. The method further comprises determining a control action that changes an upcoming state of the spacecraft to a linear combination of the non-expanding eigenvectors of the STM and generating a control command to an actuator of the spacecraft.

Classes IPC  ?

• B64G 1/24 - Appareils de guidage ou de commande, p. ex. de commande d'assiette
• B64G 1/64 - Systèmes pour réunir ou séparer des véhicules spatiaux ou des parties de ceux-ci, p. ex. aménagement pour l'accostage ou l'amarrage
• G05D 1/10 - Commande de la position ou du cap dans les trois dimensions simultanément

Abrégé

The present disclosure provides a system and a method for monitoring an operation of a vapor compression cycle. The method comprises collecting digital representation of observed variables of the operation of the vapor compression cycle over multiple instances of time and executing a constrained ensemble Kalman smoother for each instance of time to estimate the state variables of the vapor compression cycle for each instance of time. The constrained ensemble Kalman smoother updates the state variables over a sequence of time instances within a smoothing window by solving a series of constrained optimization problems in a range of a covariance, for which constraints are enforced for every variable in the smoothing window for every instance of the constrained optimization problems. The method further comprises outputting, based on the estimates of the state variables, estimates of variables of the vapor compression cycle at each instance of time.

Classes IPC  ?

• F25B 49/02 - Disposition ou montage des dispositifs de commande ou de sécurité pour machines, installations ou systèmes du type à compression

Abrégé

To control a motion of a device subject to constraints, a sequence of states and corresponding control inputs are transformed into a lifted space to determine a linear model of the dynamics of the device in the lifted space by minimizing fitting errors between the lifted states and approximation of the lifted states according to the linear control law. The fitting errors define an error model as a function bounding a data-driven envelope of a Lipschitz continuity on the fitting errors allowing to solve an optimal control problem in the lifted space according to the linear model subject to the constraints reformulated based on an evolution of the error model. The control input in the lifted space is transformed back to the original space for control.

Classes IPC  ?

• G05B 19/4155 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par le déroulement du programme, c.-à-d. le déroulement d'un programme de pièce ou le déroulement d'une fonction machine, p. ex. choix d'un programme

Abrégé

A control system for controlling a legged robot comprises a processor and a memory. The control system initializes, in response to receiving a task, a probabilistic filter with parameters associated with a state of a reference trajectory of the legged robot, wherein the parameters are predetermined for the task and encode the reference trajectory including a combination of different reference trajectories for coordinated motion primitives of different actuators of the legged robot moving the legged robot according to the task, decodes the parameters to generate the reference trajectory, and executes, in response to receiving a feedback signal, the probabilistic filter to iteratively track the state of the reference trajectory satisfying a performance objective with respect to the state of the legged robot to update the parameters.

Classes IPC  ?

• G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
• B25J 9/16 - Commandes à programme
• B62D 57/032 - Véhicules caractérisés par des moyens de propulsion ou de prise avec le sol autres que les roues ou les chenilles, seuls ou en complément aux roues ou aux chenilles avec moyens de propulsion en prise avec le sol, p. ex. par jambes mécaniques avec une base de support et des jambes soulevées alternativement ou dans un ordre déterminéVéhicules caractérisés par des moyens de propulsion ou de prise avec le sol autres que les roues ou les chenilles, seuls ou en complément aux roues ou aux chenilles avec moyens de propulsion en prise avec le sol, p. ex. par jambes mécaniques avec des pieds ou des patins soulevés alternativement ou dans un ordre déterminé

Abrégé

A computer-implemented method is provided for designing a metalens. The metalens has a metasurface including nano-structures arranged on a substrate based on preliminary simulation data. The method includes partitioning the nano-structures into overlapping d-unit supercells such that every non-perimeter nano-structure is at the center of one d-unit supercell, computing a differentiable mapping function of the d-unit supercells that predicts the near-field over the unit cell at the center of the supercell from the design parameters of all the nanostructures in the supercell, by fitting an interpolator to preliminary simulation data of the d-unit supercells, jointly tuning the design parameters of all unit cells in the metalens to better approximate a target near field distribution over the entire metalens, by using a Jacobian of partial derivatives provided by the mapping function to solve for a locally optimal correction of all design parameters, and generating a fabricable design of the metalens based on the optimized parameters.

Classes IPC  ?

• G02B 1/00 - Éléments optiques caractérisés par la substance dont ils sont faitsRevêtements optiques pour éléments optiques
• G06F 30/20 - Optimisation, vérification ou simulation de l’objet conçu

Abrégé

A reconfigurable device is provided for splitting optical beams. The device includes an input port configured to receive an input beam including at least two primary wavelengths, a tunable splitter configured to separate the input beam into at least two beams via at least two routes corresponding to the at least two primary wavelengths, wherein each of the at least two routes is configured to propagate one of the at least two primary wavelengths of the input beam, wherein the tunable splitter includes a bottom electrode, a substrate on the bottom electrode, core segments arranged on the substrate, a top layer, support segments to connect the substrate and the top layer, a top electrode on the top layer, a controllable refractive index layer arranged to fill gaps between the substrate, the support segments, and the top layer; and at least two output ports configured to transmit the at least two beams propagated via the at least two routes.

Classes IPC  ?

• G06N 3/0455 - Réseaux auto-encodeursRéseaux encodeurs-décodeurs
• G02F 1/137 - Dispositifs ou dispositions pour la commande de l'intensité, de la couleur, de la phase, de la polarisation ou de la direction de la lumière arrivant d'une source lumineuse indépendante, p. ex. commutation, ouverture de porte ou modulationOptique non linéaire pour la commande de l'intensité, de la phase, de la polarisation ou de la couleur basés sur des cristaux liquides, p. ex. cellules d'affichage individuelles à cristaux liquides caractérisés par l'effet électro-optique ou magnéto-optique, p. ex. transition de phase induite par un champ, effet d'orientation, interaction entre milieu récepteur et matière additive ou diffusion dynamique
• G06N 3/088 - Apprentissage non supervisé, p. ex. apprentissage compétitif

Abrégé

Communication-capable devices such as commercial Wi-Fi devices can be used for integrated sensing and communications (ISAC) systems to jointly exchange data and monitor environment. Such devices typically require diverse signal processing such as machine learning inference that demands high-power operations for real-time sensing and computing. The present invention provides a way to realize energy-efficient computing by exploiting the capability of data communications to access distributed computing resources including classical computers and quantum computers over networks. The system and method are based on the realization that computationally intensive processing is offloaded to networked hybrid classical-quantum computing to build dynamic computing graphs. Some embodiments use automated classical-quantum machine learning whose circuits and hyperparameters are automatically adjusted via gradient or heuristic optimization for Wi-Fi indoor monitoring and human tracking. For some embodiments, the system and method can reduce the power consumption and the number of trainable parameters by integrating classical and quantum neural networks. For some embodiments, signal processing such as denoising, filtering and detection is realized with hybrid classical-quantum processers over networks.

Classes IPC  ?

• G06N 10/60 - Algorithmes quantiques, p. ex. fondés sur l'optimisation quantique ou les transformées quantiques de Fourier ou de Hadamard

Abrégé

The present disclosure provides a system and a method for controlling a motion of a device from an initial state to a target state in an environment having obstacles that form constraints on the motion of the device. The method includes executing a learned function trained with machine learning to generate a feasible or infeasible trajectory connecting the initial state of the device with the target state of the device while penalizing an extent of violation of at least some of the constraints to produce an initial trajectory. The method further includes solving a convex optimization problem subject to the constraints to produce an optimal trajectory that minimizes deviation from the initial trajectory and controlling the motion of the device according to the optimal trajectory.

Classes IPC  ?

• G05D 1/10 - Commande de la position ou du cap dans les trois dimensions simultanément
• G06F 17/11 - Opérations mathématiques complexes pour la résolution d'équations
• G06N 3/08 - Méthodes d'apprentissage
• B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial

Abrégé

The present disclosure provides a system and a method for motion prediction for autonomous driving. The system disclosed herein provides an efficient deep-neural-network-based system to jointly perform perception and motion prediction from 3D point clouds. This system is able to take a pair of LiDAR sweeps as input and outputs for each point in the second sweep, both a classification of the point into one of a set of semantic classes, and a motion vector indicating the motion of the point within the world coordinate system. The system includes a spatiotemporal pyramid network, which extracts deep spatial and temporal features in a hierarchical fashion. The training of this system is regularized with spatial and temporal consistency losses. Thus providing an improved motion planner for autonomous driving applications.

Classes IPC  ?

• G06T 7/20 - Analyse du mouvement
• G06V 10/80 - Fusion, c.-à-d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
• G06T 7/10 - DécoupageDétection de bords
• B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes

Abrégé

A computer-implemented method using a reinforcement learning trained reduced order estimator (RL-trained ROE) and a closure model is provided for controlling a heating, ventilation, and air conditioning (HVAC) system including actuators. The method uses a processor coupled with a memory storing instructions implementing the method, wherein the instructions, when executed by the processor, carry out at steps of the method, includes acquiring setpoints of the HVAC system from a user input and measurement data from sensors arranged in the HVAC system, A computer-implemented method using a reinforcement learning trained reduced order estimator (RL-trained ROE) and a closure model is provided for controlling a heating, ventilation, and air conditioning (HVAC) system including actuators. The method uses a processor coupled with a memory storing instructions implementing the method, wherein the instructions, when executed by the processor, carry out at steps of the method, includes acquiring setpoints of the HVAC system from a user input and measurement data from sensors arranged in the HVAC system, computing a high-dimensional state estimate using the measurement data and an estimate of reduced-order state from the RL-trained ROE, determining a controller with respect to the setpoints by using the RL-trained ROE, generating control commands based on the controller, and transmitting the control commands to the actuators of HVAC system via an output interface.

Classes IPC  ?

• G05B 13/02 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
• G05B 13/04 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques impliquant l'usage de modèles ou de simulateurs
• G06N 20/00 - Apprentissage automatique
• F24F 11/63 - Traitement électronique

Abrégé

A system for controlling a motion of a trailer-based vehicle from an initial state till a target state, wherein each state includes a location and a heading of the trailer-based vehicle. The trailer-based vehicle includes a tractor and at least one trailer attached to the tractor such that the motion of the tractor controls the motion of the trailer. The system is configured to collect a set of motion primitives parameterized on quantized pseudo-trailer-configuration from a finite set of quantized pseudo-trailer-configurations, and repetitively select a node based on corresponding cost, and apply motion primitives at the selected node based on corresponding pseudo-trailer-configuration to add new nodes having pseudo-trailer-configurations belonging to set of all possible values. The system is configured to connect a sequence of multiple motion primitives into motion path connecting initial state with target state and control the motion of the tractor-trailer according to the motion path.

Classes IPC  ?

• B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant
• B60W 40/10 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés au mouvement du véhicule
• B60W 30/18 - Propulsion du véhicule

Abrégé

The present disclosure provides a system and a method for controlling a motion of a robot from a starting point to a target point within a bounded space with a floorplan including one or multiple obstacles. The method includes solving for an electric potential in a bounded virtual space formed by scaling the floorplan of the bounded space with the one or multiple obstacles and applying charge to at least one bound of the bounded virtual space while treating the scaled obstacles as metallic surfaces with a constant potential value, wherein the electric potential provides multiple equipotential curves within the bounded virtual space. The method further includes selecting an equipotential curve with a potential value different from a potential value of an obstacle equipotential curve, determining a motion path based on the selected equipotential curve, and controlling the motion of the robot based on the determined motion path.

Classes IPC  ?

• B25J 9/16 - Commandes à programme
• B25J 5/00 - Manipulateurs montés sur roues ou sur support mobile
• B62D 15/02 - Indicateurs de direction ou aides de direction

Abrégé

A controller uses a motion trajectory for controlling a motion of a device to perform a task subject to constraints. The controller evaluates a parametric function to output predicted values for a set of discrete variables in a mixed-integer convex programming (MICP) problem for performing the task defined by the parameters. The controller fixes a first subset of discrete variables in the MICP to the predicted values outputted by the trained parametric function and updates at least some of the predicted values of a remaining subset of discrete variables to values are uniquely defined by the fixed values for the first subset of discrete variables and the constraints. Hence, the controller transforms the MICP into a convex programming (CP) problem, solves the CP problem subject to the constraints to produce a feasible motion trajectory, and controls the device according to the motion trajectory.

Classes IPC  ?

• G05B 15/02 - Systèmes commandés par un calculateur électriques

Abrégé

Embodiments of the present disclosure disclose a system and method for extraction of a target sound signal. The system collects collect a mixture of sound signals. The system selects a query identifying the target sound signal to be extracted from the mixture of sound signals, the query comprising one or more identifiers. Each identifier is present in a predetermined set of one or more identifiers and defines at least one of mutually inclusive and mutually exclusive characteristics of the mixture of sound signals. The system determined one or more logical operators connecting the extracted one or more identifiers. The system transforms the one or more identifiers and the extracted logical operators into a digital representation. The system executes a neural network trained to extract the target sound signal by mixing the digital representation with intermediate outputs of intermediate layers of the neural network.

Classes IPC  ?

• G10L 21/0272 - Séparation du signal de voix
• G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels

Abrégé

The present disclosure provides a system and a method for jointly controlling one or multiple connected autonomous vehicles (CAVs) and one or multiple manual connected vehicles (MCVs) moving to form traffic on the same or intersecting roads. The method includes collecting states of each of the CAVs, each of the MCVs, and each of traffic signs regulating the traffic, and solving a multi-variable mixed-integer problem (MIP) optimizing a cost function for values of control commands changing states of each CAV and values of control commands changing states of each of the traffic signs. The cost function is optimized subject to a motion model of each of the CAVs, subject to constraints modeling general traffic rules, subject to timing constraints, and subject to a motion model of each MCV. The method further includes transmitting the optimized values of the control commands to the corresponding CAVs and corresponding traffic signs.

Classes IPC  ?

• G08G 1/16 - Systèmes anticollision
• G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
• B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
• B60W 30/18 - Propulsion du véhicule
• B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant

Abrégé

A computer-implemented method is provided for discovering heterogenous neighbors in coexisting IoT networks including at least one Wi-Fi device and at least one of Zigbee coordinators, ZigBee routers and ZigBee end devices. The method includes generating a broadcast packet such that the broadcast packet emulates a ZigBee broadcast frame, transmitting the emulated broadcast packet using a transceiver of the at least one Wi-Fi device according to cross-technology communication (CTC) method, wherein the emulated broadcast packet is configured to trigger the at least one of the Zigbee coordinators and ZigBee routers having received the emulated broadcast packet to rebroadcast the received packet. The method also includes generating a unicast packet such that the unicast packet emulates a ZigBee address request frame, transmitting the emulated unicast packet using a transceiver of the at least one Wi-Fi device according to cross-technology communication (CTC) method, wherein the emulated unicast packet is configured to trigger the at least one of the Zigbee coordinators, ZigBee routers and ZigBee end devices having received the emulated unicast packet to respond with a ZigBee address response frame, and determining the at least one ZigBee end device to be a neighbor of the at least one Wi-Fi device if the scanned address response frame is transmitted by the at least one ZigBee end device.

Classes IPC  ?

• H04W 8/00 - Gestion de données relatives au réseau
• H04L 27/26 - Systèmes utilisant des codes à fréquences multiples
• H04W 4/80 - Services utilisant la communication de courte portée, p. ex. la communication en champ proche, l'identification par radiofréquence ou la communication à faible consommation d’énergie

Abrégé

A computer-implemented method is provided for performing energy disaggregation of a distribution system-level net-load measurements using continuous-point-on-wave (CPOW) measurement units. The method uses a processor coupled with a memory stored instructions implementing the method using neural networks including an encoder network, a featuer extractor, a separator network, a decoder network stored in the memory, wherein the instructions, when executed by the processor carry out at steps of the method include generating net-load time series data from voltage and current measurements via the CPOW measurement units, generating a compressed latent space representation from the net-load time series, converting the net-load time series into time-frequency domain, passing time domain cotextual information with the converted time-frequency domain representation of net-load time series to the feature extractor, estimating two weight matrices to be multiplied with an output from the encoder network and learning temporal features of a native load and a photovoltaic (PV) generation, transforming weighted latent representation corresponding the native load and the PV generation into time-domain representations, and predicting the native load and the PV generation at distribution system-level from the transformed time domain representations corresponding to the native load and PV generations.

Classes IPC  ?

• H02J 3/00 - Circuits pour réseaux principaux ou de distribution, à courant alternatif
• H02J 3/38 - Dispositions pour l’alimentation en parallèle d’un seul réseau, par plusieurs générateurs, convertisseurs ou transformateurs
• G06Q 50/06 - Fourniture d’énergie ou d’eau
• G06N 3/04 - Architecture, p. ex. topologie d'interconnexion

Abrégé

Provided herein is a method for controlling a manipulator, comprising accepting an initial pose of a load and a task for moving the load and retrieving using a mapping function, an identification trajectory corresponding to the initial pose of the load and controlling a plurality of actuators of the manipulator to move the load according to the retrieved identification trajectory and obtaining measured motion data and estimated motion data of the load each corresponding to motion of the load. The method further comprises estimating parameters of the load based on the measured motion data and the estimated motion data, obtaining a model of the manipulator having the load with the estimated parameters, and determining a performance trajectory to move the load according to the task based on the obtained model of the manipulator. The method further comprises controlling the actuators to move the load according to the performance trajectory.

Classes IPC  ?

• B25J 9/16 - Commandes à programme

Abrégé

The present disclosure provides a system and a method for detecting and tracking objects. The method includes permuting an order of frames in a sequence of radar image frames to produce multiple permuted sequences with different frames at a dominant position in a corresponding permuted sequence of radar image frames. Each permuted sequence of radar image frames is processed with a first neural network to produce temporally enhanced features for each of the frames in the sequence of radar image frames. Further a feature map is reconstructed from the temporally enhanced features of each of the frames in the sequence of radar image frames to produce a sequence of feature maps. The method further includes processing a list of feature vectors from each feature map with a second neural network to produce temporally enhanced heatmaps.

Classes IPC  ?

• G01S 13/72 - Systèmes radar de poursuiteSystèmes analogues pour la poursuite en deux dimensions, p. ex. combinaison de la poursuite en angle et de celle en distance, radar de poursuite pendant l'exploration
• G06N 3/045 - Combinaisons de réseaux
• G06T 7/277 - Analyse du mouvement impliquant des approches stochastiques, p. ex. utilisant des filtres de Kalman

Abrégé

A system and method for low-latency audio signal enhancement is provided. An input mixture of audio signals is partitioned into a sequence of overlapping frames by using a first sliding window method. The first sliding window method comprises a first window function having a first width associated with a window of the corresponding frame and a shift length associated with shifting of the window of the first sliding window method. Each frame is then processed using a first DNN, a frequency domain causal linear filter and a second DNN, to generate final enhanced overlapping frames for each of the processed frames. The final enhanced overlapping frames are then combined using a second sliding window method associated with a second window function having a second width less than the first width and the same shift length as the first sliding window method.

Classes IPC  ?

• G10L 21/0232 - Traitement dans le domaine fréquentiel
• H04S 3/00 - Systèmes utilisant plus de deux canaux, p. ex. systèmes quadriphoniques
• H04R 1/40 - Dispositions pour obtenir la fréquence désirée ou les caractéristiques directionnelles pour obtenir la caractéristique directionnelle désirée uniquement en combinant plusieurs transducteurs identiques
• H04R 3/00 - Circuits pour transducteurs
• G10L 25/30 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par la technique d’analyse utilisant des réseaux neuronaux