AN ADAPTIVE TIME DELAY WAVELET NEURAL NETWORK FOR SIGNAL APPROXIMATION
用于信号逼近的自适应时延小波神经网络

Wavelet neural networks (WNN) is a powerful tool for function approximation. In this paper a new model named adaptive time delay WNN(ATDWNN) is proposed which combines tune delay neural network and wavelet decomposition. ATDWNN is used to approximate signals having different time delays hi the same class. In order to train ATDWNN, time mechanism based competition learning is also proposed. It is shown through experiments that ATDWNN can not only approximate signals having different time delays by th'e same superwavelet, but also detect these time delays successfully.