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| A NEW MODIFIED ELMAN NEURAL NETWORK MODEL |
| Wang Changhong①; Gao Xiaozhi①; Xu Lixin①; Zhuang Xianyi①; Gao Xiaoming② |
| ①Department of Control Engineering, P. O. Box 329, Harbin Institute of Technology Harbin 150001;②Helsinki University of Technology, Faculty of Electrical Engineering,Laboratory of Signal Processing and Computer Technology（STI）,Otakaari 5A,FIN-02150,Espoo, Finland |
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Abstract This paper first discusses the structure, principle and learning algorithm of Elman neural network model. A modified Ehnan neural network model is then proposed by adding new adjustable weights between the context nodes and the output nodes to enhance its dynamical character. The corresponding learning algorithm is also derived by using steepest descent principle. Theoretical analysis and simulation results show that this kind of modified Ehnan neural network learns much faster than the original model.
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Received: 11 December 1995
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1997, Vol. 19 
