AN ADAPTIVE TIME DELAY WAVELET NEURAL NETWORK FOR SIGNAL APPROXIMATION

He Zhenya; Li Wenhua; Wei Chengjian

Volume 20 Issue 5

Sep. 1998

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He Zhenya, Li Wenhua, Wei Chengjian . AN ADAPTIVE TIME DELAY WAVELET NEURAL NETWORK FOR SIGNAL APPROXIMATION[J]. Journal of Electronics & Information Technology, 1998, 20(5): 604-610.

Citation:

He Zhenya, Li Wenhua, Wei Chengjian . AN ADAPTIVE TIME DELAY WAVELET NEURAL NETWORK FOR SIGNAL APPROXIMATION[J]. Journal of Electronics & Information Technology, 1998, 20(5): 604-610.

He Zhenya, Li Wenhua, Wei Chengjian . AN ADAPTIVE TIME DELAY WAVELET NEURAL NETWORK FOR SIGNAL APPROXIMATION[J]. Journal of Electronics & Information Technology, 1998, 20(5): 604-610.

Citation:

He Zhenya, Li Wenhua, Wei Chengjian . AN ADAPTIVE TIME DELAY WAVELET NEURAL NETWORK FOR SIGNAL APPROXIMATION[J]. Journal of Electronics & Information Technology, 1998, 20(5): 604-610.

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AN ADAPTIVE TIME DELAY WAVELET NEURAL NETWORK FOR SIGNAL APPROXIMATION

Received Date: 1996-07-02
Rev Recd Date: 1997-12-08
Publish Date: 1998-09-19

Abstract

Abstract

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 time delay neural network and wavelet decomposition. ATDWNN is used to approximate signals having different time delays in 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 the same superwavelet, but also detect these time delays successfully.

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References(1)

References

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