Matches 1 - 50 out of 148 1 2 3 >


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US20150206050 CONFIGURING NEURAL NETWORK FOR LOW SPIKING RATE  
A method for selecting a neuron model with a user defined firing rate for operating in a neural network includes selecting the neuron model based on a selected firing rate bandwidth.
US20160140438 Hyper-class Augmented and Regularized Deep Learning for Fine-grained Image Classification  
Systems and methods are disclosed for training a learning machine by augmenting data from fine-grained image recognition with labeled data annotated by one or more hyper-classes, performing...
US20130151448 APPARATUS AND METHODS FOR IMPLEMENTING LEARNING FOR ANALOG AND SPIKING SIGNALS IN ARTIFICIAL NEURAL NETWORKS  
Apparatus and methods for universal node design implementing a universal learning rule in a mixed signal spiking neural network. In one implementation, at one instance, the node apparatus,...
US20080288427 FORMING A SIGNATURE OF PARAMETERS EXTRACTED FROM INFORMATION  
A method of storing information relating to the transmission of messages by an entity over a given time period comprises the step of creating a signature comprising a plurality of parameters...
US20160358070 AUTOMATIC TUNING OF ARTIFICIAL NEURAL NETWORKS  
Tuning a neural network may include selecting a portion of a first neural network for modification to increase computational efficiency and generating, using a processor, a second neural network...
US20160328645 REDUCED COMPUTATIONAL COMPLEXITY FOR FIXED POINT NEURAL NETWORK  
A method of reducing computational complexity for a fixed point neural network operating in a system having a limited bit width in a multiplier-accumulator (MAC) includes reducing a number of bit...
US20160247064 NEURAL NETWORK TRAINING METHOD AND APPARATUS, AND RECOGNITION METHOD AND APPARATUS  
Disclosed is a neural network training method and apparatus, and recognition method and apparatus. The neural network training apparatus receives data and train a neural network based on remaining...
US20160026912 WEIGHT-SHIFTING MECHANISM FOR CONVOLUTIONAL NEURAL NETWORKS  
A processor includes a processor core and a calculation circuit. The processor core includes logic determine a set of weights for use in a convolutional neural network (CNN) calculation and scale...
US20140143193 METHOD AND APPARATUS FOR DESIGNING EMERGENT MULTI-LAYER SPIKING NETWORKS  
Certain aspects of the present disclosure support a technique for designing an emergent multi-layer spiking neural network. Parameters of the neural network can be first determined based upon...
US20130151449 APPARATUS AND METHODS FOR IMPLEMENTING LEARNING FOR ANALOG AND SPIKING SIGNALS IN ARTIFICIAL NEURAL NETWORKS  
Apparatus and methods for universal node design implementing a universal learning rule in a mixed signal spiking neural network. In one implementation, at one instance, the node apparatus,...
US20160042271 ARTIFICIAL NEURONS AND SPIKING NEURONS WITH ASYNCHRONOUS PULSE MODULATION  
A method for configuring an artificial neuron includes receiving a set of input spike trains comprising asynchronous pulse modulation coding representations. The method also includes generating...
US20150278680 TRAINING, RECOGNITION, AND GENERATION IN A SPIKING DEEP BELIEF NETWORK (DBN)  
A method of distributed computation includes computing a first set of results in a first computational chain with a first population of processing nodes and passing the first set of results to a...
US20110077484 Systems And Methods For Identifying Non-Corrupted Signal Segments For Use In Determining Physiological Parameters  
According to embodiments, non-corrupted signal segments are detected by a data modeling processor implementing an artificial neural network. The neural network may be trained to detect artifact in...
US20170098158 SYSTEMS AND METHODS FOR A COMPUTER UNDERSTANDING MULTI MODAL DATA STREAMS  
Systems and methods for understanding (imputing meaning to) multi modal data streams may be used in intelligent surveillance and allow a) real-time integration of streaming data from video, audio,...
US20160335538 NEURAL NETWORKING SYSTEM AND METHODS  
A method/apparatus/system for generating a request for improvement of a data object in a neural network is described herein. The neural network contains a plurality of data objects each made of an...
US20160335534 NEURAL SENSOR HUB SYSTEM  
Systems and methods for a sensor hub system that accurately and efficiently performs sensory analysis across a broad range of users and sensors and is capable of recognizing a broad set of...
US20160034812 LONG SHORT-TERM MEMORY USING A SPIKING NEURAL NETWORK  
A method for configuring long short-term memory (LSTM) in a spiking neural network includes decoding input spikes into analog values within the LSTM. The method further includes implementing the...
US20140258194 GENERIC METHOD FOR DESIGNING SPIKE-TIMING DEPENDENT PLASTICITY (STDP) CURVES  
Methods and apparatus are provided for designing spike-timing dependent plasticity (STDP) curves whose parameter values are based on a set of equations. One example method generally includes...
US20130151450 NEURAL NETWORK APPARATUS AND METHODS FOR SIGNAL CONVERSION  
Apparatus and methods for universal node design implementing a universal learning rule in a mixed signal spiking neural network. In one implementation, at one instance, the node apparatus,...
US20130018833 NEURAL NETWORK SYSTEM AND METHOD FOR CONTROLLING OUTPUT BASED ON USER FEEDBACK  
For various information sources, information output based on user feedback about information from the sources is controlled. A neural network module selects object(s) to receive information from...
US20170004399 LEARNING METHOD AND APPARATUS, AND RECORDING MEDIUM  
A learning method for a multilayer neural network, implemented by a computer, includes starting first learning with an initial value of a learning rate, and maintaining the learning rate at the...
US20160071005 EVENT-DRIVEN TEMPORAL CONVOLUTION FOR ASYNCHRONOUS PULSE-MODULATED SAMPLED SIGNALS  
A method of processing asynchronous event-driven input samples of a continuous time signal, includes calculating a convolutional output directly from the event-driven input samples. The...
US20150269482 ARTIFICIAL NEURAL NETWORK AND PERCEPTRON LEARNING USING SPIKING NEURONS  
A method for communicating a non-binary value in a spiking neural network includes encoding, with an encoder, a non-binary value as one or more spikes of at least one pre-synaptic neuron in a...
US20150242741 IN SITU NEURAL NETWORK CO-PROCESSING  
A method of executing co-processing in a neural network comprises swapping a portion of the neural network to a first processing node for a period of time. The method also includes executing the...
US20170132512 REGULARIZING MACHINE LEARNING MODELS  
Methods, systems, and apparatus, including computer programs encoded on computer storage medium, for training a neural network, wherein the neural network is configured to receive an input data...
US20150269485 COLD NEURON SPIKE TIMING BACK-PROPAGATION  
Neuron state updates are computed with spiking models with map based updates and at least one reset mechanism. Back propagation is applied on spike times to compute weight updates.
US20150324691 NEURAL NETWORK CONNECTIONS USING NONVOLATILE MEMORY DEVICES  
A system includes a plurality of nonvolatile memory cells and a map that assigns connections between nodes of a neural network to the memory cells. Memory devices containing nonvolatile memory...
US20070282771 Method and Apparatus for Interpreting Information  
A method of processing data relating to a plurality of examples using a data classifier arranged to classify input data into one of a number of classes, and a rule inducer, comprising the steps...
US20120083933 METHOD AND SYSTEM TO PREDICT POWER PLANT PERFORMANCE  
The present disclosure relates to the use of hybrid predictive models to predict one or more of performance, availability, or degradation of a power plant or a component of the power plant. The...
US20080301075 METHOD OF TRAINING A NEURAL NETWORK AND A NEURAL NETWORK TRAINED ACCORDING TO THE METHOD  
A neural network comprises trained interconnected neurons. The neural network is configured to constrain the relationship between one or more inputs and one or more outputs of the neural network...
US20160335539 NEURAL NETWORKING SYSTEM AND METHODS  
A method/apparatus/system for generating a request for improvement of a data object in a neural network is described herein. The neural network contains a plurality of data objects each made of an...
US20150324690 Deep Learning Training System  
Training large neural network models by providing training input to model training machines organized as multiple replicas that asynchronously update a shared model via a global parameter server...
US20140025613 APPARATUS AND METHODS FOR REINFORCEMENT LEARNING IN LARGE POPULATIONS OF ARTIFICIAL SPIKING NEURONS  
Neural network apparatus and methods for implementing reinforcement learning. In one implementation, the neural network is a spiking neural network, and the apparatus and methods may be used for...
US20120066163 TIME TO EVENT DATA ANALYSIS METHOD AND SYSTEM  
A time to event data analysis method and system. The present invention relates to the analysis of data to identify relationships between the input data and one or more conditions. One method of...
US20170147921 LEARNING APPARATUS, RECORDING MEDIUM, AND LEARNING METHOD  
A learning apparatus includes: a learning performing unit configured to learn parameters of a multilayer neural network with regularization; a determining unit configured to determine whether...
US20170091619 SELECTIVE BACKPROPAGATION  
The balance of training data between classes for a machine learning model is modified. Adjustments are made at the gradient stage where selective backpropagation is utilized to modify a cost...
US20150269480 IMPLEMENTING A NEURAL-NETWORK PROCESSOR  
Certain aspects of the present disclosure support a method and apparatus for implementing kortex neural network processor within an artificial nervous system. According to certain aspects, a...
US20170083813 ELECTRONIC NEURAL NETWORK CIRCUIT HAVING A RESISTANCE BASED LEARNING RULE CIRCUIT  
An apparatus is described. The apparatus includes a semiconductor chip. The semiconductor chip includes spiking neural network circuitry. The spiking neural network circuitry includes a learning...
US20160098633 DEEP LEARNING MODEL FOR STRUCTURED OUTPUTS WITH HIGH-ORDER INTERACTION  
Methods and systems for training a neural network include pre-training a bi-linear, tensor-based network, separately pre-training an auto-encoder, and training the bi-linear, tensor-based network...
US20170154262 RESIZING NEURAL NETWORKS  
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for resizing neural network layers, the method including obtaining data specifying a trained neural...
US20170132515 LEARNING SYSTEM, LEARNING PROGRAM, AND LEARNING METHOD  
In a learning system, a storage stores training data. At least one processor performs a plurality of processes. Each of the processes calculates, based on the at least one parameter at a present...
US20150220831 SHORT-TERM SYNAPTIC MEMORY BASED ON A PRESYNAPTIC SPIKE  
A method for creating and maintaining short term memory using short term plasticity, includes changing a gain of a synapse based on presynaptic spike activity without regard to postsynaptic spike...
US20150026100 SYSTEM AND METHOD FOR VIEWING, MODIFYING, STORING, AND RUNNING ARTIFICIAL NEURAL NETWORK COMPONENTS  
A system and method for artificial neural network processing includes, for example, modifying, by a computer processor, a value of a charge of a node of an artificial neural depending on a number...
US20170185895 System and Method for Training Parameter Set in Neural Network  
A system and a method for training a parameter set in a neural network includes a main-control-node set, used for controlling a training process and storing a data set and a parameter set that are...
US20170161607 SYSTEM AND METHOD FOR IMPROVED GESTURE RECOGNITION USING NEURAL NETWORKS  
According to various embodiments, a method for gesture recognition using a neural network is provided. The method comprises a training mode and an inference mode. In the training mode, the method...
US20170140273 SYSTEM AND METHOD FOR AUTOMATIC SELECTION OF DEEP LEARNING ARCHITECTURE  
A system and method of determining a neural network configuration may include receiving at least one neural network configuration, altering the received configuration for at least two iterations,...
US20140344203 NEURAL NETWORK COMPUTING APPARATUS AND SYSTEM, AND METHOD THEREFOR  
In order to provide a neural network computing apparatus and system, as well as a method therefor, which operate via a synchronization circuit in which all components are synchronized with one...
US20100312736 Critical Branching Neural Computation Apparatus and Methods  
A neural network comprising artificial neurons interconnected by connections, wherein each artificial neuron is configured to receive an input signal from and send an output signal to one or more...
US20170140261 SYSTEMS, METHODS AND COMPUTER PRODUCTS FOR DETERMINING AN ACTIVITY  
Media content is recommended based on suitability for a designated activity. A vector engine is trained using a plurality of lists, each of the lists containing metadata associated with a...
US20150242745 EVENT-BASED INFERENCE AND LEARNING FOR STOCHASTIC SPIKING BAYESIAN NETWORKS  
A method of performing event-based Bayesian inference and learning includes receiving input events at each node. The method also includes applying bias weights and/or connection weights to the...

Matches 1 - 50 out of 148 1 2 3 >