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《JOURNAL OF UNIVERSITY OF SCIENCE AND TECHNOLOGY BEIJING》 2000-01
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A Fast Algorithm for Recurrent Neural Networks

WANG Ju, LIU Heping Information Engineering School, UST Beijing, Beijing 100083, China  
A new fast learning algorithm for recurrent neural networks is proposed. By introducing the signal flow graphs technique, it overcomes the disadvantage of complexity of the gradient of the error function. And for more fast convergence, the BFGS method is used. Simulation results show that the proposed algorithm converges faster than the traditional algorithm.
【Fund】: 国家“八五”攻关资助!No.85-311-02-11-04
【CateGory Index】: TP183
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