UPDATING AN ARTIFICIAL NEURAL NETWORK USING FLEXIBLE FIXED POINT REPRESENTATION
    1.
    发明申请
    UPDATING AN ARTIFICIAL NEURAL NETWORK USING FLEXIBLE FIXED POINT REPRESENTATION 审中-公开
    使用灵活的固定点表示更新人工神经网络

    公开(公告)号:US20170061279A1

    公开(公告)日:2017-03-02

    申请号:US14597091

    申请日:2015-01-14

    CPC classification number: G06N3/084

    Abstract: Updating an artificial neural network is disclosed. A node characteristic is represented using a fixed point node characteristic parameter. A network characteristic is represented using a fixed point network characteristic parameter. The fixed point node characteristic parameter and the fixed point network characteristic parameter are processed to determine a fixed point intermediate parameter having a larger size than either the fixed point node characteristic parameter or the fixed point network characteristic parameter. A value associated with the fixed point intermediate parameter is truncated according to a system truncation schema. The artificial neural network is updated according to the truncated value.

    Abstract translation: 公开了更新人造神经网络。 使用固定点节点特征参数来表示节点特性。 使用固定点网络特性参数表示网络特性。 处理固定点节点特征参数和固定点网络特征参数,以确定具有比固定点节点特征参数或固定点网络特征参数大的大小的固定点中间参数。 与固定点中间参数相关联的值根据系统截断模式被截断。 人工神经网络根据截断值进行更新。

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