Global exponential stability of recurrent neural networks with infinite time-varying delays and reaction-diffusion terms

Authors:
Qiankun Song;Zhenjiang Zhao;Xuedong Chen
Affiliations:
Department of Mathematics, Huzhou University, Huzhou, Zhejiang, China;Department of Mathematics, Huzhou University, Huzhou, Zhejiang, China;Department of Mathematics, Huzhou University, Huzhou, Zhejiang, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Year:
2005

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Abstract

The global exponential stability is discussed for a general class of recurrent neural networks with infinite time-varying delays and reaction-diffusion terms. Several new sufficient conditions are obtained to ensure global exponential stability of the equilibrium point of recurrent neural networks with infinite time-varying delays and reaction-diffusion terms. The results extend the earlier publications. In addition, an example is given to show the effectiveness of the obtained results.