STABILITY FOR THE MIX-DELAYED COHEN-GROSSBERG NEURAL NETWORKS WITH NONLINEAR IMPULSE

In this paper, the authors are concerned with the stability of the mix-delayed Cohen- Grossberg neural networks with nonlinear impulse by the nonsmooth analysis. Some novel sufficient conditions are obtained for the existence and the globally asymptotic stability of the unique equilibrium point, whi...

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Bibliographic Details
Published in:Journal of systems science and complexity 2010-06, Vol.23 (3), p.665-680
Main Authors: Zhao, Yong, Lu, Qishao, Feng, Zhaosheng
Format: Article
Language:English
Subjects:
Complex Systems
Control
Mathematics
Mathematics and Statistics
Mathematics of Computing
Operations Research/Decision Theory
Statistics
Systems Theory
全局指数稳定性
全局渐近稳定
脉冲神经网络
脉冲系统
非光滑分析
非线性脉冲
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Summary:In this paper, the authors are concerned with the stability of the mix-delayed Cohen- Grossberg neural networks with nonlinear impulse by the nonsmooth analysis. Some novel sufficient conditions are obtained for the existence and the globally asymptotic stability of the unique equilibrium point, which include the well-known results on some impulsive systems and non-impulsive systems as its particular cases. The authores also analyze the globally exponential stability of the equilibrium point. Two examples are exploited to illustrate the feasibility and effectiveness of our results.
ISSN:1009-6124
1559-7067
DOI:10.1007/s11424-010-0151-x