Global exponential stability of impulsive high-order Hopfield type neural networks with delays

被引：10
|
作者：
Xu, Bingji [1 ]
Liu, Xiang [2 ]
Teo, Kok Lay [3 ]
机构：
[1] China Univ Geosci, Sch Informat Engn, Beijing 100083, Peoples R China
[2] Huazhong Univ Sci & Technol, Inst Educ Res, Wuhan 430074, Peoples R China
[3] Curtin Univ Technol, Dept Math & Stat, Perth, WA 6845, Australia
来源：
COMPUTERS & MATHEMATICS WITH APPLICATIONS | 2009年 / 57卷 / 11-12期
基金：
中国国家自然科学基金;
关键词：
Impulsive high-order Hopfield type neural networks; Exponential stability; Lyapunov function; Delay;
D O I：
10.1016/j.camwa.2008.10.001
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, we investigate the global exponential stability of impulsive high-order Hopfield type neural networks with delays. By establishing the impulsive delay differential inequalities and using the Lyapunov method, two sufficient conditions that guarantee global exponential stability of these networks are given, and the exponential convergence rate is also obtained. A numerical example is given to demonstrate the validity of the results. (c) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1959 / 1967
页数：9
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