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    Classifying features using a neurosynaptic system
    71.
    发明授权
    Classifying features using a neurosynaptic system 有权

    公开(公告)号：US10115054B2

    公开(公告)日：2018-10-30

    申请号：US14322778

    申请日：2014-07-02

    申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION

    发明人： Rathinakumar Appuswamy ,  Steven K. Esser ,  Dharmendra S. Modha

    IPC分类号： G06N3/063 ,  G06N3/04

    摘要： Embodiments of the invention provide a method comprising receiving a set of features extracted from input data, training a linear classifier based on the set of features extracted, and generating a first matrix using the linear classifier. The first matrix includes multiple dimensions. Each dimension includes multiple elements. Elements of a first dimension correspond to the set of features extracted. Elements of a second dimension correspond to a set of classification labels. The elements of the second dimension are arranged based on one or more synaptic weight arrangements. Each synaptic weight arrangement represents effective synaptic strengths for a classification label of the set of classification labels. The neurosynaptic core circuit is programmed with synaptic connectivity information based on the synaptic weight arrangements. The core circuit is configured to classify one or more objects of interest in the input data.

    TRANSFORM ARCHITECTURE FOR MULTIPLE NEUROSYNAPTIC CORE CIRCUITS
    74.
    发明申请
    TRANSFORM ARCHITECTURE FOR MULTIPLE NEUROSYNAPTIC CORE CIRCUITS 审中-公开

    公开(公告)号：US20170228636A1

    公开(公告)日：2017-08-10

    申请号：US15184908

    申请日：2016-06-16

    申请人： International Business Machines Corporation

    发明人： Rathinakumar Appuswamy ,  Myron D. Flickner ,  Dharmendra S. Modha

    IPC分类号： G06N3/063 ,  G06F17/16 ,  G06N3/08

    摘要： Embodiments of the present invention provide a method for feature extraction using multiple neurosynaptic core circuits including one or more input core circuits for receiving input and one or more output core circuits for generating output. The method comprises receiving a set of input data via the input core circuits, and extracting a first set of features from the input data using the input core circuits. Each feature of the first set of features is based on a subset of the input data. The method further comprises reordering the first set of features using the input core circuits, and generating a second set of features by combining the reordered first set of features using the output core circuits. The second set of features comprises a set of features with reduced correlation. Each feature of the second set of features is based on the entirety of said set of input data.

    Transform for a neurosynaptic core circuit
    76.
    发明授权
    Transform for a neurosynaptic core circuit 有权
    转换为神经突触核心电路

    公开(公告)号：US09406015B2

    公开(公告)日：2016-08-02

    申请号：US14142609

    申请日：2013-12-27

    申请人： International Business Machines Corporation

    发明人： Rathinakumar Appuswamy ,  Myron D. Flickner ,  Dharmendra S. Modha

    IPC分类号： G06F15/18 ,  G06N3/04 ,  G06N3/063 ,  G06N99/00

    CPC分类号： G06N3/04 ,  G06F17/16 ,  G06N3/049 ,  G06N3/063 ,  G06N3/088

    摘要： Embodiments of the present invention provide a method for feature extraction comprising generating synaptic connectivity information for a neurosynaptic core circuit. The core circuit comprises one or more electronic neurons, one or more electronic axons, and an interconnect fabric including a plurality of synapse devices for interconnecting the neurons with the axons. The method further comprises initializing the interconnect fabric based on the synaptic connectivity information generated, and extracting a set of features from input received via the electronic axons. The set of features extracted comprises a set of features with reduced correlation.

    摘要翻译： 本发明的实施例提供了一种用于特征提取的方法，包括产生用于神经突触核心电路的突触连接信息。 核心电路包括一个或多个电子神经元，一个或多个电子轴突，以及包括用于将神经元与轴突互连的多个突触装置的互连结构。 该方法还包括基于产生的突触连接信息来初始化互连结构，以及经由电子轴突接收的输入提取一组特征。 所提取的特征集包括具有降低的相关性的一组特征。

    CLASSIFYING FEATURES USING A NEUROSYNAPTIC SYSTEM
    77.
    发明申请
    CLASSIFYING FEATURES USING A NEUROSYNAPTIC SYSTEM 审中-公开
    使用神经系统的分类特征

    公开(公告)号：US20160004962A1

    公开(公告)日：2016-01-07

    申请号：US14322778

    申请日：2014-07-02

    申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION

    发明人： Rathinakumar Appuswamy ,  Steven K. Esser ,  Dharmendra S. Dharmendra

    IPC分类号： G06N3/08 ,  G06N3/04

    CPC分类号： G06N3/08 ,  G06N3/04 ,  G06N3/049 ,  G06N3/063

    摘要： Embodiments of the invention provide a method comprising receiving a set of features extracted from input data, training a linear classifier based on the set of features extracted, and generating a first matrix using the linear classifier. The first matrix includes multiple dimensions. Each dimension includes multiple elements. Elements of a first dimension correspond to the set of features extracted. Elements of a second dimension correspond to a set of classification labels. The elements of the second dimension are arranged based on one or more synaptic weight arrangements. Each synaptic weight arrangement represents effective synaptic strengths for a classification label of the set of classification labels. The neurosynaptic core circuit is programmed with synaptic connectivity information based on the synaptic weight arrangements. The core circuit is configured to classify one or more objects of interest in the input data

    摘要翻译： 本发明的实施例提供了一种方法，包括接收从输入数据中提取的一组特征，基于提取的特征集来训练线性分类器，以及使用线性分类器生成第一矩阵。 第一个矩阵包括多个维度。 每个维度都包含多个元素。 第一维的元素对应于提取的特征集合。 第二维的元素对应于一组分类标签。 第二维度的元件基于一个或多个突触重量布置来布置。 每个突触体重排列表示分类标签集合的分类标签的有效突触强度。 基于突触重量排列，神经突触核心电路被编程为突触连接信息。 核心电路被配置为对输入数据中的一个或多个感兴趣对象进行分类