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    • 4. 发明授权
    • Method for training a neural network
    • 训练神经网络的方法
    • US06968327B1
    • 2005-11-22
    • US10049650
    • 2000-08-24
    • Ronald KatesNadia HarbeckManfred Schmitt
    • Ronald KatesNadia HarbeckManfred Schmitt
    • A61B5/00G06F19/00G06N3/08G06E1/00G06E3/00G06F15/18G06G7/00
    • G06N3/08A61B5/00A61B5/415A61B5/418A61B5/7267G06F19/00
    • A method for training a neural network in order to optimize the structure of the neural network includes identifying and eliminating synapses that have no significant influence on the curve of the risk function. First and second sending neurons are selected that are connected to the same receiving neuron by respective first and second synapses. It is assumed that there is a correlation of response signals from the first and second sending neurons to the same receiving neuron. The first synapse is interrupted and a weight of the second synapse is adapted in its place. The output signals of the changed neural network are compared with the output signals of the unchanged neural network. If the comparison result does not exceed a predetermined level, the first synapse is eliminated, thereby simplifying the structure of the neural network.
    • 用于训练神经网络以优化神经网络的结构的方法包括识别和消除对风险函数的曲线没有显着影响的突触。 选择通过相应的第一和第二突触连接到相同接收神经元的第一和第二发送神经元。 假设存在来自第一和第二发送神经元到相同接收神经元的响应信号的相关性。 第一突触中断,第二突触的重量适应其位置。 将改变的神经网络的输出信号与不变神经网络的输出信号进行比较。 如果比较结果不超过预定水平,则消除第一突触,从而简化了神经网络的结构。