Global exponential stability of Hopfield neural networks with variable delays and impulsive effects

被引：9
|
作者：
Yang Zhi-chun [1 ]
Xu Dao-yi
机构：
[1] Chongqing Normal Univ, Math Coll, Chongqing 40047, Peoples R China
[2] Sichuan Univ, Yangtze Ctr Math, Chengdu 610064, Peoples R China
来源：
APPLIED MATHEMATICS AND MECHANICS-ENGLISH EDITION | 2006年 / 27卷 / 11期
基金：
中国国家自然科学基金;
关键词：
neural networks; impulse; delay; stability;
D O I：
10.1007/s10483-006-1109-1
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A class of Hopfield neural network with time-varying delays and impulsive effects is concerned. By applying the piecewise continuous vector Lyapunov function some sufficient conditions were obtained to ensure the global exponential stability of impulsive delay neural networks. An example and its simulation are given to illustrate the effectiveness of the results.
引用
收藏
页码：1517 / 1522
页数：6
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