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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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【Citations】
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1 LING Wei-xin 1, ZHENG Qi-lun 2, CHEN Qiong 2, LU Cui-ying 1 (1. Dept. of Applied Mathematics, South China Univ. of Tech., Guangzhou 510640, China; 2. Dept. of Computer Engineering and Science, South China Univ. of Tech., Guangzhou 510640, China);A Modular Neural Network Architecture Based on Parallel Cooperation[J];Journal of Beijing University of Posts and Telecommunications;2002-02
【Co-references】
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1 ZUO Yun-bo,ZHANG Huai-cun (Department of Mechanical Engineering, Beijing Institute of Machinery, Beijing 100085 , China);An improved rapid algorithm for BP network[J];Journal of Beijing Institute of Machinery;2005-01
2 WANG Yan, LIU Jinglu, SUN Yikang (Information Engineering School, UST Beijing, Beijing 100083, China) (Information Science and Engineering School, Jinan University, Jinan 250022, China) (Computer Center, Jinan University, Jinan 250022, China);Immune Genetic Algorithms(IGA)Based Scheduling Optimization for Finisher[J];Journal of University of Science and Technology Beijing;2002-03
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