Neural Simulation Environment Patents (Class 706/44)
  • Patent number: 11720343
    Abstract: In some embodiments, a method comprises receiving, at a processor of an autonomous vehicle and from at least one sensor, sensor data distributed within a time window. A first event being a first event type occurring at a first time in the time window is identified by the processor using a software model based on the sensor data. At least one first attribute associated with the first event is extracted by the processor. A second event being the first event type occurring at a second time in the time window is identified by the processor based on the at least one first attribute. In response to determining that the second event is not yet recognized as being the first event type, a first label for the second event is generated by the processor.
    Type: Grant
    Filed: November 4, 2022
    Date of Patent: August 8, 2023
    Assignee: PlusAI, Inc.
    Inventors: Gael Gurvan Colas, Mayank Gupta, Anurag Ganguli, Timothy P. Daly, Jr.
  • Patent number: 11520576
    Abstract: In some embodiments, a method comprises receiving, at a processor of an autonomous vehicle and from at least one sensor, sensor data distributed within a time window. A first event being a first event type occurring at a first time in the time window is identified by the processor using a software model based on the sensor data. At least one first attribute associated with the first event is extracted by the processor. A second event being the first event type occurring at a second time in the time window is identified by the processor based on the at least one first attribute. In response to determining that the second event is not yet recognized as being the first event type, a first label for the second event is generated by the processor.
    Type: Grant
    Filed: January 7, 2022
    Date of Patent: December 6, 2022
    Assignee: PlusAI, Inc.
    Inventors: Gael Gurvan Colas, Mayank Gupta, Anurag Ganguli, Timothy P. Daly, Jr.
  • Patent number: 11481627
    Abstract: Computer-implemented techniques for learning composite machine learned models are disclosed. Benefits to implementors of the disclosed techniques include allowing non-machine learning experts to use the techniques for learning a composite machine learned model based on a learning dataset, reducing or eliminating the explorative trial and error process of manually tuning architectural parameters and hyperparameters, and reducing the computing resource requirements and model learning time for learning composite machine learned models. The techniques improve the operation of distributed learning computing systems by reducing or eliminating straggler effects and by reducing or minimizing synchronization latency when executing a composite model search algorithm for learning a composite machine learned model.
    Type: Grant
    Filed: October 30, 2019
    Date of Patent: October 25, 2022
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Yuwei Qiu, Chengming Jiang, Huiji Gao, Bee-Chung Chen, Bo Long
  • Patent number: 11347998
    Abstract: A method to translate a nervous system model into Hardware Description Language (HDL) is presented here. The nervous system model is that produced from the Nervous System Modeling Tool, patent application Ser. No. 15/660,858, and the HDL translation downloads into either a Field Programmable Gate Array (FPGA) chip or an Application-Specific Integrated Circuit (ASIC) architecture. The method supports the neurobiological realism of Ser. No. 15/660,858 and adds massive parallelism operating at adjustable microchip speeds. A neurobiologically realistic nervous system embedded on a microchip achieves the goal of neuromorphic computing and thus embodies a nervous system on a chip. The potential applications are extensive and cover the range of robotics, big data analysis, medical diagnostics and remediation, self-learning systems, and artificially intelligent applications such as intelligent assistants.
    Type: Grant
    Filed: February 26, 2018
    Date of Patent: May 31, 2022
    Inventor: Fredric William Narcross
  • Patent number: 11340564
    Abstract: In order to control a technical system, a system state of the technical system is continually detected. By a trained first control model, a subsequent state of the technical system is predicted on the basis of a sensed system state. Then, a distance value is determined for a distance between the predicted subsequent state and an actually occurring system state. Furthermore, a second control model is trained by the trained first control model to predict the distance value on the basis of a sensed system state and on the basis of a control action for controlling the technical system. A subsequent state predicted by the first control model is then modified on the basis of a distance value predicted by the trained second control model. The modified subsequent state is output in order to control the technical system.
    Type: Grant
    Filed: December 5, 2017
    Date of Patent: May 24, 2022
    Inventors: Alexander Hentschel, Steffen Udluft, Clemens Otte
  • Patent number: 11232345
    Abstract: One embodiment relates to a neuromorphic network including electronic neurons and an interconnect circuit for interconnecting the neurons. The interconnect circuit includes synaptic devices for interconnecting the neurons via axon paths, dendrite paths and membrane paths. Each synaptic device includes a variable state resistor and a transistor device with a gate terminal, a source terminal and a drain terminal, wherein the drain terminal is connected in series with a first terminal of the variable state resistor. The source terminal of the transistor device is connected to an axon path, the gate terminal of the transistor device is connected to a membrane path and a second terminal of the variable state resistor is connected to a dendrite path, such that each synaptic device is coupled between a first axon path and a first dendrite path, and between a first membrane path and said first dendrite path.
    Type: Grant
    Filed: March 9, 2018
    Date of Patent: January 25, 2022
    Assignee: International Business Machines Corporation
    Inventors: Daniel J. Friedman, Seongwon Kim, Chung H. Lam, Dharmendra S. Modha, Bipin Rajendran, Jose A. Tierno
  • Patent number: 11229406
    Abstract: Infusion devices and related medical devices, patient data management systems, and methods are provided for monitoring a physiological condition of a patient. An exemplary method of monitoring a physiological condition of a patient involves obtaining current measurement data for the physiological condition of the patient provided by a sensing arrangement, obtaining a user input indicative of one or more future events associated with the patient, and in response to the user input, determining a prediction of the physiological condition of the patient in the future based at least in part on the current measurement data and the one or more future events using one or more prediction models associated with the patient, and displaying a graphical representation of the prediction on a display device.
    Type: Grant
    Filed: March 22, 2018
    Date of Patent: January 25, 2022
    Assignee: Medtronic MiniMed, Inc.
    Inventors: Yuxiang Zhong, Pratik Agrawal, Huzefa F. Neemuchwala, Sinu Bessy Abraham, Boyi Jiang
  • Patent number: 11182639
    Abstract: Systems, methods, and non-transitory computer-readable media can provide at least one frame of a content item to a saliency prediction model, the saliency prediction model being trained to identify salient points of interest that appear in content items. Information describing at least a first salient point of interest that appears in the at least one frame can be obtained from the saliency prediction model. The first salient point of interest can be predicted to be of interest to users accessing the content item. A view-based projection can be applied to a region corresponding to the first salient point of interest, wherein the view-based projection enhances a quality in which the region is presented.
    Type: Grant
    Filed: April 13, 2018
    Date of Patent: November 23, 2021
    Assignee: Facebook, Inc.
    Inventors: Evgeny V. Kuzyakov, Renbin Peng, Chien-Nan Chen
  • Patent number: 11176449
    Abstract: Neural network accelerator hardware-specific division of inference may be performed by operations including obtaining a computational graph and a hardware chip configuration. The operations also include dividing inference of the plurality of layers into a plurality of groups. Each group includes a number of sequential layers based on an estimate of duration and energy consumption by the hardware chip to perform inference of the neural network by performing the mathematical operations on activation data, sequentially by layer, of corresponding portions of layers of each group. The operations further include generating instructions for the hardware chip to perform inference of the neural network, sequentially by group, of the plurality of groups.
    Type: Grant
    Filed: February 26, 2021
    Date of Patent: November 16, 2021
    Assignee: EDGECORTIX PTE. LTD.
    Inventors: Nikolay Nez, Antonio Tomas Nevado Vilchez, Hamid Reza Zohouri, Mikhail Volkov, Oleg Khavin, Sakyasingha Dasgupta
  • Patent number: 10970629
    Abstract: The present disclosure is directed to reducing model size of a machine learning model with encoding. The input to a machine learning model may be encoded using a probabilistic data structure with a plurality of mapping functions into a lower dimensional space. Encoding the input to the machine learning model results in a compact machine learning model with a reduced model size. The compact machine learning model can output an encoded representation of a higher-dimensional space. Use of such a machine learning model can include decoding the output of the machine learning model into the higher dimensional space of the non-encoded input.
    Type: Grant
    Filed: February 24, 2017
    Date of Patent: April 6, 2021
    Assignee: Amazon Technologies, Inc.
    Inventors: Leo Parker Dirac, Oleg Rybakov, Vijai Mohan
  • Patent number: 10707105
    Abstract: A pick-up head array with shape memory alloy (SMA) pick-up heads is used for selective pick-up and placement of semiconductor devices. In response to the application of heat, the SMA body portions of one or more of the pick-up heads of the pick-up head array transition from a shortened state to an extended state. In the extended state, the one or more pick-up heads are able to attach to one or more LEDs on a carrier substrate. The LEDs are removed from the carrier substrate and placed onto a target substrate by the pick-up head array. Heat may be applied to the one or more pick-up heads to bond the LEDs to the target substrate. The LEDs are then detached from the pick-up head array, and heat may be removed from the one or more pick-up heads to return them to their rest state.
    Type: Grant
    Filed: February 27, 2019
    Date of Patent: July 7, 2020
    Assignee: Facebook Technologies, LLC
    Inventor: Pooya Saketi
  • Patent number: 10147035
    Abstract: A circuit for emulating the behavior of biological neural circuits, the circuit including a plurality of nodes wherein each node comprises a neuron circuit, a time multiplexed synapse circuit coupled to an input of the neuron circuit, a time multiplexed short term plasticity (STP) circuit coupled to an input of the node and to the synapse circuit, a time multiplexed Spike Timing Dependent Plasticity (STDP) circuit coupled to the input of the node and to the synapse circuit, an output of the node coupled to the neuron circuit; and an interconnect fabric coupled between the plurality of nodes for providing coupling from the output of any node of the plurality of nodes to any input of any other node of the plurality of nodes.
    Type: Grant
    Filed: June 30, 2016
    Date of Patent: December 4, 2018
    Assignee: HRL Laboratories, LLC
    Inventors: Jose Cruz-Albrecht, Timothy Derosier, Narayan Srinivasa
  • Patent number: 10068668
    Abstract: Method and apparatus for processing medical data. The method for processing indication conditions includes obtaining a plurality of predetermined indication conditions which relate to a plurality of parameters and forming a plurality of conditional segments based on respective values of the plurality of parameters, which respectively correspond to a plurality of combinations of value ranges of the plurality of parameters. The method for processing patient data includes obtaining distribution information of the patient data in the plurality of conditional segments formed above and determining a matching relationship of patient data with at least one indication condition. The apparatuses correspond to the methods.
    Type: Grant
    Filed: February 21, 2014
    Date of Patent: September 4, 2018
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Feng Cao, Xiang Li, Jing Mei, Yuan Ni, Weijia Shen, Wen Sun
  • Patent number: 9744055
    Abstract: An antagonistically actuated shape memory alloy (SMA) manipulator utilizes a pair of SMA actuators. The SMA actuators are configured, such that one actuator is trained to have a substantially linear or extended shape in its austenite phase, while the other actuator is trained to have a curved or flexed shape in its austenite phase. As such, the manipulator is operated, such that when one SMA actuator is heated and takes on its “trained” shape in the austenite phase, the other SMA actuator is permitted to cool and allowed to return to its original “untrained” shape in the martensite phase, and vice versa. This antagonistic operation of the SMA actuators allows the manipulator to achieve rapid flexion and extension movements.
    Type: Grant
    Filed: April 10, 2015
    Date of Patent: August 29, 2017
    Assignee: The University of Akron
    Inventors: Erik D. Engeberg, Savas Dilibal
  • Patent number: 9672464
    Abstract: Certain aspects of the present disclosure support efficient implementation of common neuron models. In an aspect, a first memory layout can be allocated for parameters and state variables of instances of a first neuron model, and a second memory layout different from the first memory layout can be allocated for parameters and state variables of instances of a second neuron model having a different complexity than the first neuron model.
    Type: Grant
    Filed: May 1, 2014
    Date of Patent: June 6, 2017
    Assignee: QUALCOMM Incorporated
    Inventors: Anthony Sarah, Jeffrey Alexander Levin, Jeffrey Baginsky Gehlhaar
  • Patent number: 9600762
    Abstract: A method for dynamically setting a neuron value processes a data structure including a set of parameters for a neuron model and determines a number of segments defined in the set of parameters. The method also includes determining a number of neuron types defined in the set of parameters and determining at least one boundary for a first segment.
    Type: Grant
    Filed: October 7, 2013
    Date of Patent: March 21, 2017
    Assignee: QUALCOMM INCORPORATED
    Inventors: Anthony Sarah, Jeffrey Alexander Levin
  • Publication number: 20150120632
    Abstract: An artificial neural network may be configured to test the impact of certain input parameters. To improve testing efficiency and to avoid test runs that may not alter system performance, the effect of input parameters on neurons or groups of neurons may be determined to classify the neurons into groups based on the impact of certain parameters on those groups. Groups may be ordered serially and/or in parallel based on the interconnected nature of the groups and whether the output of neurons in one group may affect the operation of another. Parameters not affecting group performance may be pruned as inputs to that particular group prior to running system tests, thereby conserving processing resources during testing.
    Type: Application
    Filed: October 28, 2013
    Publication date: April 30, 2015
    Applicant: QUALCOMM Incorporated
    Inventors: Michael CAMPOS, Casimir Matthew WIERZYNSKI, Bardia Fallah BEHABADI
  • Publication number: 20150106317
    Abstract: Aspects of the present disclosure provide methods and apparatus for allocating memory in an artificial nervous system simulator implemented in hardware. According to certain aspects, memory resource requirements for one or more components of an artificial nervous system being simulated may be determined and portions of a shared memory pool (which may include on-chip and/or off-chip RAM) may be allocated to the components based on the determination.
    Type: Application
    Filed: August 5, 2014
    Publication date: April 16, 2015
    Inventors: Venkat Rangan, Jan Krzys Wegrzyn, Jeffrey Alexander Levin, John Paul Daniels
  • Publication number: 20150058269
    Abstract: An electronic neuronal circuit system to model the interaction between the postsynaptic terminal of a first synapse between two neurons and the postsynaptic terminal of a second synapse between two neurons includes comparators to model the presynaptic neurons of the synapses, plurality of three diodes connected to the comparators to model synapses, an AND gate and latch to model the formation of functional link between the postsynaptic terminals, and timer-controlled latches for controlling the life-span of the inter-postsynaptic functional link, durations of re-activation of inter-postsynaptic functional link and flow of activity through the output postsynaptic dendritic terminals.
    Type: Application
    Filed: October 31, 2013
    Publication date: February 26, 2015
    Inventor: Kunjumon Ittira Vadakkan
  • Publication number: 20150052092
    Abstract: The invention discloses the technology of brain-like computing virtualization. Brain-like computing means the computing technology to mimic human brain and generate human intelligence automatically with computer software. Here the unconscious engine and conscious engine are used to define human left and right brain, while the virtualization technology is used for software to run on future hardware, such as quantum computer and molecular computer. The applied domain areas include quantum gate and adiabatic quantum simulation, brain-like autonomic computing, traditional multi-core-cluster performance service, software development/service delivery systems, and mission-critical business continuity/disaster recovery.
    Type: Application
    Filed: December 5, 2013
    Publication date: February 19, 2015
    Inventors: Changbin Tang, Li Xiong
  • Patent number: 8812413
    Abstract: A first array of simulated neurons having trees of output branches and a second array of simulated neurons having trees of input branches are generated. Thereafter, the output branches of one or more of the simulated neurons of the first array and the input branches of one or more of the simulated neurons of the second array are grown and connections are formed between individual output branches of the simulated neurons of the first array and individual input branches of the simulated neurons of the second array that grow to within a vicinity of each other.
    Type: Grant
    Filed: March 17, 2008
    Date of Patent: August 19, 2014
    Assignee: Evolved Machines, Inc.
    Inventors: Paul A. Rhodes, Brian Seisho Taba
  • Publication number: 20140214739
    Abstract: Embodiments of the invention relate to a function-level simulator for modeling a neurosynaptic chip. One embodiment comprises simulating a neural network using an object-oriented framework including a plurality of object-oriented classes. Each class corresponds to a component of a neural network. Running a simulation model of the neural network includes instantiating multiple simulation objects from the classes. Each simulation object is an instance of one of the classes.
    Type: Application
    Filed: November 6, 2012
    Publication date: July 31, 2014
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventor: International Business Machines Corporation
  • Publication number: 20140201118
    Abstract: Disclosed is a method for the computer-assisted modeling of a technical system. One or more output vectors are modeled dependent on one or more input vectors by the learning process of a neural network on the basis of training data of known input vectors and output vectors. Each output vector comprises one or more operating variables of the technical system, and each input vector comprises one or more input variables that influence the operating variable(s). The neural network is a feedforward network with an input layer, a plurality of hidden layers, and an output layer. The output layer comprises a plurality of output clusters, each of which consists of one or more output neurons, the plurality of output clusters corresponding to the plurality of hidden layers. Each output cluster describes the same output vector and is connected to another hidden layer.
    Type: Application
    Filed: July 24, 2012
    Publication date: July 17, 2014
    Applicant: SIEMENS AKTIENGESELLSCHAFT
    Inventors: Jochen Cleve, Ralph Grothmann, Kai Heesche, Christoph Tietz, Hans-Georg Zimmermann
  • Publication number: 20140180990
    Abstract: A simulated neural circuit includes a plurality of simulated neurons. The simulated neurons have input branches that are configured to connect to a plurality of inputs and activate in response to activity in the inputs to which they are connected. In addition, the simulated neurons are configured to activate in response to activity in their input branches. Initial connections are formed between various input branches and various inputs and a set of the inputs are activated. Thereafter, the stability of connections between input branches and inputs to which they are connected is moderated based on the activated set of inputs and a pattern of activity generated in the input branches and simulated neurons in response to the activated set of inputs.
    Type: Application
    Filed: July 8, 2013
    Publication date: June 26, 2014
    Inventor: Paul A. Rhodes
  • Patent number: 8725670
    Abstract: A method of emulating the human brain with its thought and rationalization processes is presented here, as well as a method of storing human-like thought. The invention provides for inclusion of psychological profiles, experience and societal position in an electronic emulation of the human brain. This permits a realistic human-like response by that emulation to the people and the interactive environment around it.
    Type: Grant
    Filed: June 15, 2012
    Date of Patent: May 13, 2014
    Assignee: Neuric LLC
    Inventor: Thomas A. Visel
  • Patent number: 8725658
    Abstract: A simple format is disclosed and referred to as Elementary Network Description (END). The format can fully describe a large-scale neuronal model and embodiments of software or hardware engines to simulate such a model efficiently. The architecture of such neuromorphic engines is optimal for high-performance parallel processing of spiking networks with spike-timing dependent plasticity. Methods for managing memory in a processing system are described whereby memory can be allocated among a plurality of elements and rules configured for each element such that the parallel execution of the spiking networks is most optimal.
    Type: Grant
    Filed: September 21, 2011
    Date of Patent: May 13, 2014
    Assignee: Brain Corporation
    Inventors: Eugene M. Izhikevich, Botond Szatmary, Csaba Petre, Filip Piekniewski
  • Patent number: 8712941
    Abstract: A simple format is disclosed and referred to as Elementary Network Description (END). The format can fully describe a large-scale neuronal model and embodiments of software or hardware engines to simulate such a model efficiently. The architecture of such neuromorphic engines is optimal for high-performance parallel processing of spiking networks with spike-timing dependent plasticity. The format is specifically tuned for neural systems and specialized neuromorphic hardware, thereby serving as a bridge between developers of brain models and neuromorphic hardware manufactures.
    Type: Grant
    Filed: September 21, 2011
    Date of Patent: April 29, 2014
    Assignee: Brain Corporation
    Inventors: Eugene M. Izhikevich, Csaba Petre, Filip Piekniewski, Botond Szatmary
  • Patent number: 8699566
    Abstract: Adaptive and integrated visualization of spatiotemporal data from large-scale simulation, is provided. A simulation is performed utilizing a simulator comprising multiple processors, generating spatiotemporal data samples from the simulation. Each data sample has spatial coordinates with a time stamp at a specific time resolution, and a tag. The data samples are assembled into data streams based on at least one of a spatial relationship and the corresponding tag. Each data stream is encoded into multiple formats, and an integrated and adaptive visualization of the data streams is displayed, wherein various data streams are simultaneously and synchronously displayed.
    Type: Grant
    Filed: January 27, 2010
    Date of Patent: April 15, 2014
    Assignee: International Business Machines Corporation
    Inventors: Rajagopal Ananthanarayanan, Shyamal S. Chandra, Dharmendra S. Modha, Raghavendra Singh
  • Patent number: 8688829
    Abstract: The method for binding a sensor and an actuator can be categorized into three types: manual binding, automatic binding and semi-automatic binding. Manual binding methods increase users' operational burden when a great number of sensors and actuators are to be bound. The current hard-coded automatic binding method suffers from lack of versatility. The template-based semi-automatic binding method still requires users to input some information manually. The disclosure provides an automatic binding method, which can automatically and reasonably bind the functions of a sensor and an actuator without user input, in a sensor network comprising a plurality of sensors and actuators.
    Type: Grant
    Filed: September 19, 2011
    Date of Patent: April 1, 2014
    Assignee: Industrial Technology Research Institute
    Inventors: Yueh Feng Lee, Hsin Sheng Liu, Ming Shyan Wei, Yang Jung Li
  • Publication number: 20140052679
    Abstract: Event-based updates in artificial neuron networks may be implemented. An internal event may be defined in order to update incoming connections of a neuron. The internal event may be triggered by an external signal and/or internally by the neuron. A reinforcement signal may be used to trigger an internal event of a neuron in order to perform synaptic updates without necessitating post-synaptic response. An external event may be defined in order to deliver response of the neuron to desired targets. The external and internal events may be combined into a composite event configured to effectuate connection update and spike delivery to post-synaptic target. The scope of the internal event may comprise the respective neuron and does not extend to other neurons of the network. Conversely, the scope of the external event may extend to other neurons of the network via, for example, post-synaptic spike delivery.
    Type: Application
    Filed: August 17, 2012
    Publication date: February 20, 2014
    Inventors: Oleg Sinyavskiy, Eugene Izhikevich
  • Patent number: 8583577
    Abstract: Certain aspects of the present disclosure present a technique for unsupervised training of input synapses of primary visual cortex (V1) simple cells and other neural circuits. The proposed unsupervised training method utilizes simple neuron models for both Retinal Ganglion Cell (RGC) and V1 layers. The model simply adds the weighted inputs of each cell, wherein the inputs can have positive or negative values. The resulting weighted sums of inputs represent activations that can also be positive or negative. In an aspect of the present disclosure, the weights of each V1 cell can be adjusted depending on a sign of corresponding RGC output and a sign of activation of that V1 cell in the direction of increasing the absolute value of the activation. The RGC-to-V1 weights can be positive and negative for modeling ON and OFF RGCs, respectively.
    Type: Grant
    Filed: May 25, 2011
    Date of Patent: November 12, 2013
    Assignee: QUALCOMM Incorporated
    Inventor: Vladimir Aparin
  • Patent number: 8543526
    Abstract: Systems, methods, and computer program products are provided to provide noise reduction for an input signal using a neural network. A feed-forward set of neuron groups is provided to enhance neuron activity within a particular frequency band based on prior reception of activity within that frequency band, and also to attenuate surrounding frequency bands. A surround-inhibition set of neuron groups further attenuates activity surrounding the stimulated frequency band.
    Type: Grant
    Filed: September 16, 2010
    Date of Patent: September 24, 2013
    Assignee: The Intellisis Corporation
    Inventor: Douglas A. Moore
  • Patent number: 8515886
    Abstract: Efficiently simulating an Amari dynamics of a neural field a, the Amari dynamics being specified by the equation (1) where a(x,t) is the state of the neural field a, represented in a spatial domain (SR) using coordinates x,t, i(x,i) is a function stating the input to the neural field at time t, f[.] is a bounded monotonic transfer function having values between 0 and 1, F(x) is an interaction kernel, ? specifies the time scale on which the neural field a changes and h is a constant specifying the global excitation or inhibition of the neural field a. A method comprises the step of simulating an application of the transfer function f to the neural field a. Simulating an application of the transfer function f comprises smoothing the neural field a by applying a smoothing operator (S).
    Type: Grant
    Filed: November 28, 2008
    Date of Patent: August 20, 2013
    Assignee: Honda Research Institute Europe GmbH
    Inventor: Alexander Gepperth
  • Patent number: 8504341
    Abstract: Methods, systems, and computer readable media are provided for fast updating of oil and gas field production optimization using physical and proxy simulators. A base model of a reservoir, well, or a pipeline network is established in one or more physical simulators. A decision management system is used to define uncertain parameters for matching with observed data. A proxy model is used to fit the uncertain parameters to outputs of the physical simulators, determine sensitivities of the uncertain parameters, and compute correlations between the uncertain parameters and output data from the physical simulators. Parameters for which the sensitivities are below a threshold are eliminated. The decision management system validates parameters which are output from the proxy model in the simulators. The validated parameters are used to make production decisions.
    Type: Grant
    Filed: January 31, 2007
    Date of Patent: August 6, 2013
    Assignee: Landmark Graphics Corporation
    Inventors: Alvin Stanley Cullick, William Douglas Johnson
  • Patent number: 8244402
    Abstract: A robotic system includes a humanoid robot with robotic joints each moveable using an actuator(s), and a distributed controller for controlling the movement of each of the robotic joints. The controller includes a visual perception module (VPM) for visually identifying and tracking an object in the field of view of the robot under threshold lighting conditions. The VPM includes optical devices for collecting an image of the object, a positional extraction device, and a host machine having an algorithm for processing the image and positional information. The algorithm visually identifies and tracks the object, and automatically adapts an exposure time of the optical devices to prevent feature data loss of the image under the threshold lighting conditions. A method of identifying and tracking the object includes collecting the image, extracting positional information of the object, and automatically adapting the exposure time to thereby prevent feature data loss of the image.
    Type: Grant
    Filed: September 22, 2009
    Date of Patent: August 14, 2012
    Assignees: GM Global Technology Operations LLC, The United States of America as represented by the Administrator of the National Aeronautics and Space Administration
    Inventors: James W. Wells, Neil David Mc Kay, Suhas E. Chelian, Douglas Martin Linn, Charles W. Wampler, II, Lyndon Bridgwater
  • Patent number: 8065022
    Abstract: Embodiments of the invention can include methods and systems for controlling clearances in a turbine. In one embodiment, a method can include applying at least one operating parameter as an input to at least one neural network model, modeling via the neural network model a thermal expansion of at least one turbine component, and taking a control action based at least in part on the modeled thermal expansion of the one or more turbine components. An example system can include a controller operable to determine and apply the operating parameters as inputs to the neural network model, model thermal expansion via the neural network model, and generate a control action based at least in part on the modeled thermal expansion.
    Type: Grant
    Filed: January 8, 2008
    Date of Patent: November 22, 2011
    Assignee: General Electric Company
    Inventors: Karl Dean Minto, Jianbo Zhang, Erhan Karaca
  • Publication number: 20110270790
    Abstract: Systems, methods, and computer program products are provided to provide noise reduction for an input signal using a neural network. A feed-forward set of neuron groups is provided to enhance neuron activity within a particular frequency band based on prior reception of activity within that frequency band, and also to attenuate surrounding frequency bands. A surround-inhibition set of neuron groups further attenuates activity surrounding the stimulated frequency band.
    Type: Application
    Filed: September 16, 2010
    Publication date: November 3, 2011
    Applicant: The Intellisis Corporation
    Inventor: Douglas A. MOORE
  • Patent number: 8036764
    Abstract: A method is used for providing sensing data to a control system of a machine. The method may include providing a plurality of virtual sensors, each of which may have a model type, at least one input parameter, and at least one output parameter. The method may also include integrating the plurality of virtual sensors into a virtual sensor network; determining interdependencies among the plurality of virtual sensors; and obtaining operational information of the plurality of virtual sensors. Further, the method may include determining a first condition under which the virtual sensor network is unfit to provide one or more virtual sensor output parameter to the control system based on the determined interdependencies and the operational information; and presenting the determined first condition to the control system.
    Type: Grant
    Filed: November 2, 2007
    Date of Patent: October 11, 2011
    Assignee: Caterpillar Inc.
    Inventors: Anthony J. Grichnik, James Mason, Tim Felty
  • Patent number: 8032636
    Abstract: A method, computer program product, and system are disclosed for dynamically provisioning clusters of middleware appliances. In one embodiment, the method includes referencing a resource measurement from a plurality of middleware appliances. The middleware appliances process one or more service domains and the resource measurement includes processing resources consumed by each middleware appliance for each of the one or more service domains. The method may also include determining an implementation plan based on a performance goal and one or more resource calculations. The implementation plan specifies service domain instances to activate and service domain instances to deactivate on the plurality of middleware appliances. The method may also include dynamically enabling and disabling the service domain instances on the plurality of middleware appliances based on the implementation plan.
    Type: Grant
    Filed: February 5, 2009
    Date of Patent: October 4, 2011
    Assignee: International Business Machines Corporation
    Inventors: Robert D. Callaway, Adolfo F. Rodriguez, Yannis Viniotis
  • Patent number: 8005773
    Abstract: A cortical simulator optimizing the simulation scale and time through computationally efficient simulation of neurons in a clock-driven and synapses in an event-driven fashion, memory efficient representation of simulation state, and communication efficient message exchanges.
    Type: Grant
    Filed: March 25, 2008
    Date of Patent: August 23, 2011
    Assignee: International Business Machines Corporation
    Inventors: Rajagopal (Ananth) Ananthanarayanan, Dharmendra Shantilal Modha
  • Patent number: 7970719
    Abstract: A method is described for structurally individualized simulation of the introduction of a wall support element into a section of a tubular structure. To this end, image data of the interior of the section of the tubular structure are provided. A start point and an end point of the section of the tubular structure are then determined, and a lumen and a profile line of the tubular structure are determined between the start point and the end point. Furthermore, an individual elastic structure model for the section of the tubular structure is identified by adapting a tubular elastic initial model to the section of the tubular structure on the basis of the identified lumen and the profile line, and a tubular elastic wall support element model which is positioned inside the individual structure model is provided.
    Type: Grant
    Filed: June 5, 2009
    Date of Patent: June 28, 2011
    Assignee: Siemens Aktiengesellschaft
    Inventors: Jan Egger, Bernd Freisleben, Stefan Grosskopf, Carlos Leber
  • Patent number: 7925492
    Abstract: A method for emulating human cognition in electronic form is disclosed. Information is received in the form of a textual or voice input in a natural language. This is parsed into pre-determined phrases based on a stored set of language rules for the natural language. Then, the parsed phrases are determined as to whether they define aspects of an environment and, if so, then creating weighting factors to the natural language that are adaptive, the created weighting factors operable to create a weighted decision based upon the natural language. Then it is determined if the parsed phrases constitute a query and, if so, then using the weighted factors to make a decision to the query.
    Type: Grant
    Filed: June 5, 2007
    Date of Patent: April 12, 2011
    Assignee: Neuric Technologies, L.L.C.
    Inventor: Thomas A. Visel
  • Patent number: 7908236
    Abstract: Provided are a method, system and program for using multiple data structures to manage data in cache. A plurality of data structures each have entries identifying data from a first computer readable medium added to a second computer readable medium. A request is received for data in the first computer readable medium. A determination is made as to whether there is an entry for the requested data in one of the data structures. The requested data is retrieved from the first computer readable medium to store in the second computer readable medium in response to determining that there is no entry for the requested data in one of the data structures. One of the data structures is selected in response to determining that there is no entry for the requested data in one of the data structures and an entry for the retrieved data is added to the selected data structure.
    Type: Grant
    Filed: July 20, 2006
    Date of Patent: March 15, 2011
    Assignee: International Business Machines Corporation
    Inventors: Dharmendra Shantilal Modha, Binny Sher Gill, Michael Thomas Benhase, Joseph Smith Hyde, II
  • Patent number: 7885198
    Abstract: A packet-network analyzer system for characterizing network conditions of a packet-network-under-test is provided. In this regard, one such system can be broadly summarized by a representative analyzer system that incorporates a data collection element to receive the raw digital data from a host analyzer, a data selection element to receive the raw digital data, a data processing element to process the selected data set to generate a normalized data set, a neural processing module to process the normalized data set to generate a set of rules and relationships, and a data mining module that uses the rules and relationships to generate a mined data set from the selected data set, the mined data set being used to characterize a packet-network-under test.
    Type: Grant
    Filed: January 5, 2004
    Date of Patent: February 8, 2011
    Assignee: JDS Uniphase Corporation
    Inventor: John M. Monk
  • Patent number: 7853323
    Abstract: In general, the invention is directed to a technique for selection of parameter configurations for a neurostimulator using neural networks. The technique may be employed by a programming device to allow a clinician to select parameter configurations, and then program an implantable neurostimulator to deliver therapy using the selected parameter configurations. The parameter configurations may include one or more of a variety of parameters, such as electrode configurations defining electrode combinations and polarities for an electrode set implanted in a patient. The electrode set may be carried by one or more implanted leads that are electrically coupled to the neurostimulator. In operation, the programming device executes a parameter configuration search algorithm to guide the clinician in the selection of parameter configurations. The search algorithm relies on a neural network that identifies potential optimum parameter configurations.
    Type: Grant
    Filed: June 29, 2007
    Date of Patent: December 14, 2010
    Assignee: Medtronic, Inc.
    Inventor: Steven M. Goetz
  • Patent number: 7818273
    Abstract: A cortical simulator optimizing the simulation scale and time through computationally efficient simulation of neurons in a clock-driven and synapses in an event-driven fashion, memory efficient representation of simulation state, and communication efficient message exchanges.
    Type: Grant
    Filed: September 18, 2007
    Date of Patent: October 19, 2010
    Assignee: International Business Machines Corporation
    Inventors: Rajagopal (Ananth) Ananthanarayanan, Dharmendra Shantilal Modha
  • Patent number: 7814086
    Abstract: The present disclosure is directed to systems and methods for determining semantically related terms based on sequences of search queries. Generally, a semantically related term tool examines search logs to associate search queries with a user submitting the search query. The semantically related term tool establishes a plurality of sequences of search queries, each sequence of search queries comprising one or more search queries associated with a common user and relating to a common concept. The semantically related term tool receives one or more seed terms and determines one or more terms related to the received seed terms based on the established plurality of sequences of search queries.
    Type: Grant
    Filed: November 16, 2006
    Date of Patent: October 12, 2010
    Assignee: Yahoo! Inc.
    Inventors: Kevin Bartz, Vijay Murthi, Benjamin Rey, Shaji Sebastian
  • Patent number: 7787969
    Abstract: A method is provide for providing sensors for a machine. The method may include obtaining data records including data from a plurality of sensors for the machine and determining a virtual sensor corresponding to one of the plurality of sensors. The method may also include establishing a virtual sensor process model of the virtual sensor indicative of interrelationships between at least one sensing parameters and a plurality of measured parameters based on the data records and obtaining a set of values corresponding to the plurality of measured parameters. Further, the method may include calculating the values of the at least one sensing parameters substantially simultaneously based upon the set of values corresponding to the plurality of measured parameters and the virtual sensor process model and providing the values of the at least one sensing parameters to a control system.
    Type: Grant
    Filed: June 15, 2007
    Date of Patent: August 31, 2010
    Assignee: Caterpillar Inc
    Inventors: Anthony J. Grichnik, Amit Jayachandran, Mary L. Kesse, Michael Seskin
  • Publication number: 20100211537
    Abstract: Efficiently simulating an Amari dynamics of a neural field (a), the Amari dynamics being specified by the equation (1) where a(x,t) is the state of the neural field (a), represented in a spatial domain (SR) using coordinates x,t, i(x,i) is a function stating the input to the neural field at time t, f[.] is a bounded monotonic transfer function having values between 0 and 1, F(x) is an interaction kernel, s specifies the time scale on which the neural field (a) changes and h is a constant specifying the global excitation or inhibition of the neural field (a). A method for simulating an Amari dynamics of a neural field (a), comprising the step of simulating an application of the transfer function (f) to the neural field (a). According to the invention, the step of simulating an application of the transfer function (f) comprises smoothing the neural field (a) by applying a smoothing operator (S).
    Type: Application
    Filed: November 28, 2008
    Publication date: August 19, 2010
    Applicant: HONDA RESEARCH INSTITUTE EUROPE GMBH
    Inventor: Alexander Gepperth
  • Patent number: 7774287
    Abstract: A system to move a component in accordance with a setpoint profile including a plurality of target states of the component, each of the plurality of target states to be substantially attained at one of a corresponding sequence of target times, is presented. The system includes a displacement device to move the component according to the setpoint profile; a storage device containing a library of feedforward data; a signal generating part configured to identify a plurality of time segments of the setpoint profile that correspond to entries in the library of feedforward data, and access the entries in order to construct a feedforward signal; and a feedforward control system to control the operation of the displacement device by reference to the feedforward signal constructed by the signal generating part.
    Type: Grant
    Filed: March 14, 2006
    Date of Patent: August 10, 2010
    Assignee: ASML Netherlands B.V.
    Inventors: Marcel François Heertjes, Yin-Tim Tso, Edwin Teunis Van Donkelaar