Stability for the mix-delayed Cohen-Grossberg neural networks with nonlinear impulse

被引：7

作者：

Zhao, Yong ^{[1
]}

Lu, Qishao ^{[1
]}

Feng, Zhaosheng ^{[2
]}

机构：

[1] Beijing Univ Aeronaut & Astronaut, Dept Dynam & Control, Beijing 100191, Peoples R China

[2] Univ Texas Pan Amer, Dept Math, Edinburg, TX 78539 USA

来源：

JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY | 2010年 / 23卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Asymptotic stability; equilibrium point; Lyapunov method; neural networks; nonlinear impulses; nonsmooth analysis; GLOBAL EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; DISCRETE;

D O I：

10.1007/s11424-010-0151-x

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

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.

引用

页码：665 / 680

页数：16

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