Analog neurons and neurosynaptic networks
    1.
    发明授权
    Analog neurons and neurosynaptic networks 有权
    模拟神经元和神经突触网络

    公开(公告)号:US06999953B2

    公开(公告)日:2006-02-14

    申请号:US10189749

    申请日:2002-07-03

    摘要: An analog neural computing medium, neuron and neural networks are disclosed. The neural computing medium includes a phase change material that has the ability to cumulatively respond to multiple input signals. Input signals induce transformations among a plurality of accumulation states of the disclosed neural computing medium. The accumulation states are characterized by a high electrical resistance. Upon cumulative receipt of energy from one or more input signals that equals or exceeds a threshold value, the neural computing medium fires by transforming to a low resistance state. The disclosed neural computing medium may also be configured to perform a weighting function whereby it weights incoming signals. The disclosed neurons may also include activation units for further transforming signals transmitted by the accumulation units according to a mathematical operation. The artificial neurons, weighting units, accumulation units and activation units may be connected to form artificial neural networks.

    摘要翻译: 公开了一种模拟神经计算媒介,神经元和神经网络。 神经计算介质包括具有对多个输入信号累积响应的能力的相变材料。 输入信号诱导所公开的神经计算介质的多个累积状态之间的变换。 累积状态的特征在于高电阻。 在累积接收等于或超过阈值的一个或多个输入信号的能量时,通过转换为低电阻状态来激发神经计算媒体。 所公开的神经计算介质还可以被配置为执行加权功能,由此加权输入信号。 所公开的神经元还可以包括用于根据数学运算进一步变换由累积单元发送的信号的激活单元。 可以将人造神经元,加权单元,累积单元和激活单元连接以形成人造神经网络。