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Simple Conjugation-Gradient BP Algorithm for Feedforward Neural Networks
LIANG Jiu-zhen1, HE Xin-gui2, HUANG De-shuang2*
1. Beijing University of Aeronautics and Astronautics, Dept. of Computer Science and Engineering;
2. Beijing Institute of System Engineering

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Abstract�� The high dimension of the learning error function for BP networks and the difficult computation complexity are incestigated. A simple modified conjugation-gradient decent algorithm (MPARTAN) is proposed based on improving the gradient BP algorithm. That the computation complexity of this algorithm is not higher than that of the BP momentum algorithm. Compared with FR conjugation algorithm, this algorithm has better stability and fast speed quality of convergence. It is also investigated that the convergence theorems for this algorithm and comparison of the computing results by two computing examples for the promoted three algorithms: BP momentum algorithm, FR conjugation-gradient algorithm and the novel MPARTAN algorithm.
Keywords�� neural networks   convergence   conjugate gradient method   BP algorithm   MPARTAN algorithm     
Received 1999-03-25;
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LIANG Jiu-zhen, HE Xin-gui, HUANG De-shuang.Simple Conjugation-Gradient BP Algorithm for Feedforward Neural Networks[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2000,V26(5): 596-599
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