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Discussion of stability in a class of models on recurrent wavelet neural networks
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作者 邓韧 李著信 樊友洪 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2007年第4期471-476,共6页
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.... 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. 展开更多
关键词 recurrent wavelet neural networks asymptotic stability nonlinear dynamic system Lyapunov function
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