Global exponential stability analysis of impulsive Cohen-Grossberg neural networks with delays

被引：0
|
作者：
Luo, Wenpin [1 ]
Zhong, Shouming
Liu, Xinzhi
Yan, Jun
机构：
[1] Univ Elect Sci & Technol China, Sch Appl Math, Chengdu 610054, Sichuan, Peoples R China
[2] Univ Waterloo, Dept Math Appl, Waterloo, ON N2L 3G1, Canada
来源：
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES A-MATHEMATICAL ANALYSIS | 2006年 / 13卷
关键词：
Cohen-Grossberg neural networks; exponential stability; impulsive; delay;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this Letter, a class of Cohen-Grossberg neural networks involving variable delays and impulsive effects is considered. Global exponential stability is investigated by Lyapunov function and the well-known inequalities, and the estimated exponential convergence rate is also obtained. The proposed condition generalizes some previous results in the literature. At last, a numerical example is worked out to illustrate the effectiveness of the result.
引用
收藏
页码：1561 / 1564
页数：4
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