Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2004, Vol. 27 ›› Issue (4): 87-91.

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An Improved Training Algorithm for Artificial Neural Networks

WANG Bo-tao1,2, WU Wei-ling2, WU Shan-pei2   

  1. 1. Beijing Capitel Corporation Limited, Beijing 100016, China;
    2. Information Engineering School, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2003-09-23 Online:2004-04-28

Abstract: In order to resolve the convergence speed problem due to the approximate formula in the process of the recursive least squares back propagation training algorithm(namely RLS-BP), we propose here an improved RLS-BP algorithm, which is deduced through an un-approximation formula. Experiments show that theconvergence of the improved algorithm is faster than before. The improved RLS-BP algorithm is more effective.

Key words: pattern recognition, neural network, training algorithm

CLC Number: