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�������պ����ѧѧ�� 2003, Vol. 29 Issue (3) :248-251    DOI:
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Modeling of Nonlinear System with Diagonal Recurrent Neural Network
Chen Ping, Qiu Lihua, Wang Zhanlin*
School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics

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Abstract�� Based on an analysis on the modeling principles of nonlinear system, the identification of a nonlinear system was realized with Diagonal Recurrent Neural Networks (DRNN). Serial-parallel identification architecture was applied in the modeling. Time variation was taken into account in the adjustment algorithm of weights. Compared with static neural network, the method based on DRNN displays better ability to deal with a dynamic system, due to its advantages such as without the need of system order number, a smaller neural network structure and a faster convergence. Simulation results testified the feasibility and validity of the proposed method.
Keywords�� neural networks   non-linear systems   systems identification     
Received 2001-10-10;
About author: �� ƽ(1974-),��,�����ϲ���,��ʿ��,100083,����.
��ƽ, ������, ��ռ��.���ڶԽǻع�����ķ�����ϵͳ��ģ[J]  �������պ����ѧѧ��, 2003,V29(3): 248-251
Chen Ping, Qiu Lihua, Wang Zhanlin.Modeling of Nonlinear System with Diagonal Recurrent Neural Network[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2003,V29(3): 248-251
http://bhxb.buaa.edu.cn//CN/     ��     http://bhxb.buaa.edu.cn//CN/Y2003/V29/I3/248
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