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    Handling signal saturation in spiking neural networks
    71.
    发明授权
    Handling signal saturation in spiking neural networks 有权

    公开(公告)号：US10679119B2

    公开(公告)日：2020-06-09

    申请号：US15468838

    申请日：2017-03-24

    Applicant: INTEL CORPORATION

    Inventor： Arnab Paul ,  Narayan Srinivasa

    IPC: G06N3/04

    Abstract: The present disclosure provides for generating a spiking neural network. Generating a spiking neural network can include determining that a first input fan-in from a plurality of input neurons to each of a plurality of output neurons is greater than a threshold, generating a plurality of intermediate neurons based on a determination that the first input fan-in is greater than the threshold, and coupling the plurality of intermediate neurons to the plurality of input neurons and the plurality of output neurons, wherein each of the plurality of intermediate neurons has a second input fan-in that is less than the first input fan-in and each of the plurality of output neurons has a third input fan-in that is less than the first input fan-in.

    OBJECT RECOGNITION USING A SPIKING NEURAL NETWORK
    77.
    发明申请
    OBJECT RECOGNITION USING A SPIKING NEURAL NETWORK 审中-公开

    公开(公告)号：US20180276530A1

    公开(公告)日：2018-09-27

    申请号：US15468881

    申请日：2017-03-24

    Applicant: INTEL CORPORATION

    Inventor： Arnab Paul ,  Narayan Srinivasa

    IPC: G06N3/04 ,  G06N3/08

    CPC classification number: G06N3/049 ,  G06N3/08 ,  G06N3/088

    Abstract: Embodiments described herein describe object recognition using a spiking neural network. Object recognition using a spiking neural network can include processing each of the plurality of base templates through a plurality of input neurons to generate a plurality of first spikes through the plurality of input neurons, providing the plurality of first spikes from the plurality of input neurons to each of a plurality of excitatory neurons (E-neurons), providing a plurality of second spikes from a plurality of inhibitory neurons (I-neurons) to the plurality of E-neurons to inhibit a spiking rate of the E-neurons, generating a plurality of weights at each of the plurality of E-neurons based on the plurality of first spikes and the plurality of second spikes, and classifying a pattern utilizing the plurality of input neurons, the plurality of E-neurons, and the plurality of weights at each of the E-neurons.

    SUPERVISED TRAINING AND PATTERN MATCHING TECHNIQUES FOR NEURAL NETWORKS
    78.
    发明申请
    SUPERVISED TRAINING AND PATTERN MATCHING TECHNIQUES FOR NEURAL NETWORKS 审中-公开

    公开(公告)号：US20180174042A1

    公开(公告)日：2018-06-21

    申请号：US15385334

    申请日：2016-12-20

    Applicant: Intel Corporation

    Inventor： Narayan Srinivasa ,  Yongqiang Cao ,  Andreas Wild

    IPC: G06N3/08 ,  G06N3/04

    CPC classification number: G06N3/08 ,  G06N3/0454 ,  G06N3/049

    Abstract: Systems and methods for supervised learning and cascaded training of a neural network are described. In an example, a supervised process is used for strengthening connections to classifier neurons, with a supervised learning process of receiving a first spike at a classifier neuron from a processing neuron in response to training data, and receiving an out-of-band communication of a second desired (artificial) spike at the classifier neuron that corresponds to the classification of the training data. As a result of spike timing dependent plasticity, connections to the classifier neuron are strengthened. In another example, a cascaded technique is disclosed to generate a plurality of trained neural networks that are separately initialized and trained based on different types or forms of training data, which may be used with cascaded or parallel operation of the plurality of trained neural networks.

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