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动态非线性连续时间系统的小波神经网络辨识
引用本文:张兆宁,喻文焕,郁惟镛.动态非线性连续时间系统的小波神经网络辨识[J].控制理论与应用,2002,19(5):709-712.
作者姓名:张兆宁  喻文焕  郁惟镛
作者单位:1. 上海交通大学,电力工程系,上海,200030
2. 天津大学,数学系,天津,300072
基金项目:国家自然科学基金(69774012)资助项目.
摘    要:将小波神经网络应用于动态非线性连续时间系统的辨识, 同时为了使神经网络的训练达到全局最优和加速小波神经网络训练的收敛速度, 提出了信赖域算法, 并研究了信赖域算法的收敛性. 随后进行了算例仿真, 证明了所提辨识方法的有效性.

关 键 词:小波    神经网络    非线性连续时间系统    辨识
文章编号:1000-8152(2002)05-0709-04
收稿时间:2000/9/26 0:00:00
修稿时间:6/4/2001 12:00:00 AM

Continuous time nonlinear system identification with wavelet neural networks
ZHANG Zhao-ning,YU Wen-huan and YU Wei-yong.Continuous time nonlinear system identification with wavelet neural networks[J].Control Theory & Applications,2002,19(5):709-712.
Authors:ZHANG Zhao-ning  YU Wen-huan and YU Wei-yong
Affiliation:Department of Electric Power Engineering,Shanghai Jiaotong University,Shanghai 200030,China;Department of Mathematics,Tianjin University,Tianjing 300072,China;Department of Electric Power Engineering,Shanghai Jiaotong University,Shanghai 200030,China
Abstract:The wavelet neural networks are used for identification of continuous time nonlinear systems. For the improvement of convergent speed and the global optimization in the training of wavelet neural networks, the trust region algorithm is proposed for the training. Then we study the convergence properties about the trust region algorithm. Finally, the simulation results are given to illustrate the efficiency of the method proposed.
Keywords:wavelets  neural networks  nonlinear continuous time system  identification
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