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    TRAINING, RECOGNITION, AND GENERATION IN A SPIKING DEEP BELIEF NETWORK (DBN)
    21.
    发明申请
    TRAINING, RECOGNITION, AND GENERATION IN A SPIKING DEEP BELIEF NETWORK (DBN) 审中-公开
    在深入比较网络（DBN）中的训练，识别和生成

    公开(公告)号：US20150278680A1

    公开(公告)日：2015-10-01

    申请号：US14659516

    申请日：2015-03-16

    Applicant: QUALCOMM Incorporated

    Inventor： Venkata Sreekanta Reddy ANNAPUREDDY ,  David Jonathan JULIAN ,  Anthony SARAH

    IPC: G06N3/04 ,  G06N3/08

    CPC classification number: G06N3/0454 ,  G06N3/049 ,  G06N3/088

    Abstract: 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 second population of processing nodes. The method also includes entering a first rest state with the first population of processing nodes after passing the first set of results and computing a second set of results in the first computational chain with the second population of processing nodes based on the first set of results. The method further includes passing the second set of results to the first population of processing nodes, entering a second rest state with the second population of processing nodes after passing the second set of results and orchestrating the first computational chain.

    Abstract translation: 一种分布式计算的方法包括：在具有第一种处理节点的第一计算链中计算第一组结果，并将第一组结果传递给第二种处理节点。 该方法还包括在传递第一组结果之后，与处理节点的第一群体一起输入第一休息状态，并且基于第一组结果与第二种处理节点计算第一计算链中的第二组结果。 该方法还包括将第二组结果传递给第一处理节点群，在通过第二组结果并编排第一计算链之后，与第二处理节点群进入第二休息状态。

    ARTIFICIAL NEURAL NETWORK AND PERCEPTRON LEARNING USING SPIKING NEURONS
    23.
    发明申请
    ARTIFICIAL NEURAL NETWORK AND PERCEPTRON LEARNING USING SPIKING NEURONS 审中-公开
    人工神经网络和PERCEPTRON学习使用SPIKING神经元

    公开(公告)号：US20150269482A1

    公开(公告)日：2015-09-24

    申请号：US14526312

    申请日：2014-10-28

    Applicant: QUALCOMM Incorporated

    Inventor： Venkata Sreekanta Reddy ANNAPUREDDY ,  David Jonathan JULIAN

    IPC: G06N3/08

    CPC classification number: G06N3/049

    Abstract: 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 temporal frame. The method also includes computing a value with a decoder matched to the encoder. The value is computed by at least one post-synaptic neuron. The value is based on at least one synaptic weight and on the encoded spikes received from the pre-synaptic neuron.

    Abstract translation: 用于在尖峰神经网络中传达非二进制值的方法包括使用编码器将非二进制值编码为时间帧中至少一个突触前神经元的一个或多个尖峰。 该方法还包括使用与编码器匹配的解码器来计算值。 该值由至少一个突触后神经元计算。 该值基于至少一个突触重量和从突触前神经元接收的编码峰值。

    METHODS AND APPARATUS FOR IMPLEMENTATION OF GROUP TAGS FOR NEURAL MODELS
    25.
    发明申请
    METHODS AND APPARATUS FOR IMPLEMENTATION OF GROUP TAGS FOR NEURAL MODELS 有权
    用于实施神经模型组标签的方法和装置

    公开(公告)号：US20150088796A1

    公开(公告)日：2015-03-26

    申请号：US14268152

    申请日：2014-05-02

    Applicant: QUALCOMM INCORPORATED

    Inventor： David Jonathan JULIAN ,  Jeffrey Alexander LEVIN ,  Jeffrey Baginsky GEHLHAAR

    IPC: G06N3/04 ,  G06N3/08

    CPC classification number: G06N3/049 ,  G06N3/0454

    Abstract: Certain aspects of the present disclosure support assigning neurons and/or synapses to group tags where group tags have an associated set of parameters. By using group tags, neurons or synapses in a population can be assigned a group tag. Then, by changing a parameter associated with the group tag, all synapses or neurons in the group may have that parameter changed.

    Abstract translation: 本公开的某些方面支持将神经元和/或突触分配给组标签，其中组标签具有相关联的参数集合。 通过使用组标签，群体中的神经元或突触可以被分配一个组标签。 然后，通过更改与组标签相关联的参数，组中的所有突触或神经元可能会改变该参数。

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