A Modified Backpropagation Training Algorithm for Feedforward Neural Networks*

被引：0
|
作者：
T. Kathirvalavakumar
P. Thangavel
机构：
[1] V.H.N.S.N. College,Department of Computer Science
[2] University of Madras,Department of Computer Science
来源：
Neural Processing Letters | 2006年 / 23卷
关键词：
linear error; modified standard backpropagation; nonlinear error; optimization criterion; single hidden layer network;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, a new efficient learning procedure for training single hidden layer feedforward network is proposed. This procedure trains the output layer and the hidden layer separately. A new optimization criterion for the hidden layer is proposed. Existing methods to find fictitious teacher signal for the output of each hidden neuron, modified standard backpropagation algorithm and the new optimization criterion are combined to train the feedforward neural networks. The effectiveness of the proposed procedure is shown by the simulation results.
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页码：111 / 119
页数：8
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