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《Journal of Beijing University of Posts and Telecommunications》 2004-04
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An Improved Training Algorithm for Artificial Neural Networks

WANG Bo-tao~(1,2),WU Wei-ling~2,WU Shan-pei~2 (1. Beijing Capitel Corporation Limited, Beijing 100016, China; 2. Information Engineering School, Beijing University of Posts and Telecommunications, Beijing 100876, China)  
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 the convergence of the improved algorithm is faster than before. The improved RLS-BP algorithm is more effective.
【Fund】: 首信博士后基金(0111)
【CateGory Index】: TP183
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