A Comparison between Neural Networks and Wavelet Networks in Nonlinear System Identification

Hamed Khodadadi ； S. Ehsan Razavi ； Hossein Ahmadi-Noubari

《Research Journal of Applied Sciences, Engineering and Technology》 4卷9期 (2012/05) Pp. 1021-1026

並列摘要

In this study, identification of a nonlinear function will be presented by neural network and wavelet network methods. Behavior of a nonlinear system can be identified by intelligent methods. Two groups of the most common and at the same time the most effective of neural networks methods are multilayer perceptron and radial basis function that will be used for nonlinear system identification. The selected structure is series-parallel method that after network training by a series of training random data, the output is estimated and the nonlinear function is compared to a sinusoidal input. Then, wavelet network is used for identification and we will use Orthogonal Least Squares (OLS) method for wavelet selection to reduce the volume of calculations and increase the convergence speed.

並列關鍵字

Nonlinear identification ； nonlinear ARX model ； orthogonal least squares ； radial basis function ； wavelet network