Backpropagation algorithm for a generalized neural network structure

K. Krishnakumar
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引用次数: 4

Abstract

The author presents a generalized neural network structure and the associated backpropagation learning algorithm. This structure is an extension of a neural net structure presented by P.J. Werbos (1988, 1990). Generalization is aimed at ease of implementation and flexibility in structure selection. It is shown how certain network structures can be accommodated using this general structural form. Networks that are investigated include feedforward, recurrent, and memory networks.<>
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广义神经网络结构的反向传播算法
提出了一种广义神经网络结构及其反向传播学习算法。该结构是P.J. Werbos(1988,1990)提出的神经网络结构的扩展。泛化的目的是为了便于实现和结构选择的灵活性。它显示了如何使用这种一般结构形式来适应某些网络结构。研究的网络包括前馈网络、循环网络和记忆网络
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