Applied Mathematics and Mechanics (English Edition) ›› 2007, Vol. 28 ›› Issue (4): 471-476 .doi: https://doi.org/10.1007/s10483-007-0407-z

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Discussion of stability in a class of models on recurrent wavelet neural networks

DENG Ren, LI Zhu-xin, FAN You-hong   

  1. Logistic Engineering University, Chongqing 400016, P. R. China
  • Received:2005-01-20 Revised:2006-10-26 Online:2007-04-18 Published:2007-04-18
  • Contact: LI Zhu-xin

Abstract: Based on wavelet neural networks (WNNs) and recurrent neural networks (RNNs), a class of models on recurrent wavelet neural networks (RWNNs) is proposed. The new networks possess the advantages of WNNs and RNNs. In this paper, asymptotic stability of RWNNs is researched according to the Lyapunov theorem, and some theorems and formulae are given. The simulation results show the excellent performance of the networks in nonlinear dynamic system recognition.

2010 MSC Number: 

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