基于小波神经网络的系统辨识方法

WAVELET NEURAL NETWORKS BASED SYSTEM IDENTIFICATION

神经网络由于具有良好的自学习和自适应能力，在非线性黑箱建模或系统辨识中有着广泛的应用，这些辨识模型有：多层感知器、径向基函数网和反馈网络等等．文中提出了基于小波神经网络模型的系统辨识方法．由于小波变换或分解所表现的良好的时频局部化特性，以及多尺度的功能，我们用规范正交的小波函数作为基函数网络中的基函数，得到所谓的小波神经网络．

Neural networks show good ability of selfadaption and selflearning, and is widely applied in nonlinear blackbox modeling and system identification. This paper proposes a wavelet neural networks based system identification method. Because of the time frenqency location characteristic and multiscale ability of wavelet transformation and muliresolution analysis, wavelet is used as the basic of the basis neural networks, and we call it wavelet neural networks. First the paper gives the general framework of the proplem of nonlinear blackbox modeling system identificaiton, then uses wavelet neural networks as the blackbox model, and at last the computer simulation results show that the method is practical.