Discussion of Stability in a Class of Models on Recurrent Wavelet Neural Networks

DENG Ren; LI Zhu-xin; FAN You-hong

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DENG Ren, LI Zhu-xin, FAN You-hong. Discussion of Stability in a Class of Models on Recurrent Wavelet Neural Networks[J]. Applied Mathematics and Mechanics, 2007, 28(4): 428-432.

Citation:

DENG Ren, LI Zhu-xin, FAN You-hong. Discussion of Stability in a Class of Models on Recurrent Wavelet Neural Networks[J]. Applied Mathematics and Mechanics, 2007, 28(4): 428-432.

Citation:

DENG Ren, LI Zhu-xin, FAN You-hong. Discussion of Stability in a Class of Models on Recurrent Wavelet Neural Networks[J]. Applied Mathematics and Mechanics, 2007, 28(4): 428-432.

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Discussion of Stability in a Class of Models on Recurrent Wavelet Neural Networks

Logistic Engineering University, Chongqing 400016, R. P. China

Received Date: 2005-01-20
Rev Recd Date: 2006-10-22
Publish Date: 2007-04-15

Abstract

Abstract

Based on wavelet neural networks (WNNs) and recurrent neural networks (RNNs), a class of models on recurrent wavelet neural networks (RWNNs) was proposed. The new networks possess the advantages of WNNs and RNNs. Asymptotic stability of RWNNs was researched according to the Liapunov theorem. Some theorems and formulae were given. The simulation results show the excellent performance of the networks in nonlinear dynamic system recognition.
- recurrent wavelet neural networks,
- asymptotic stability,
- nonlinear dynamic system,
- Liapunov function

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References(5)

References

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