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1. 发明授权

US4912651A Speeding learning in neural networks 失效
标题翻译：加速神经网络学习
公开(公告)号：US4912651A
公开(公告)日：1990-03-27
申请号：US284148
申请日：1988-12-14
申请人： Laurence F. Wood , Michael J. Grimaldi , Eric D. Peterson
发明人： Laurence F. Wood , Michael J. Grimaldi , Eric D. Peterson
IPC分类号： G06N3/08
CPC分类号： G06N3/084
摘要： A method of accelerating the training of an artificial neural network uses a computer configured as an artificial neural network with a network input and a network output, and having a plurality of interconnected units arranged in layers including an input layer and an output layer. Each unit has a multiplicity of unit inputs and a set of variables for operating upon a unit inputs to provide a unit output. A plurality of examples are serially provided to the network input and the network output is observed. The computer is programmed with a back propagation algorithm for adjusting each set of variables in response to feedback representing differences between the network output for each example and the desired output. The examples are iterated until the signs of the outputs of the units of the output layer converge. Then each set of variables is multiplied by a multiplier. The examples are reiterated until the magnitude of the outputs of the units of the output layer converge.
摘要翻译：一种加速人工神经网络的训练的方法使用配置为具有网络输入和网络输出的人造神经网络的计算机，并且具有布置成包括输入层和输出层的层的多个互连单元。每个单元具有多个单位输入和一组用于在单位输入上运行以提供单位输出的变量。将多个示例串行提供给网络输入，并且观察网络输出。计算机被编程有反向传播算法，用于响应于表示每个示例的网络输出与期望输出之间的差异的反馈来调整每组变量。迭代示例，直到输出层的单位输出的符号收敛。然后每组变量乘以乘数。重复这些示例，直到输出层的单位的输出的大小收敛。

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