The existence and stability of the anti-periodic solution for delayed Cohen-Grossberg neural networks with impulsive effects

被引：36
|
作者：
Abdurahman, Abdujelil [1 ]
Jiang, Haijun [1 ]
机构：
[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Xinjiang, Peoples R China
来源：
NEUROCOMPUTING | 2015年 / 149卷
关键词：
Cohen-Grossberg neural network; Anti-periodic solution; Exponential stability; Impulsive effect; Time-varying delay; GLOBAL EXPONENTIAL STABILITY; PERIODIC-SOLUTION;
D O I：
10.1016/j.neucom.2013.09.071
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we investigate the existence and global exponential stability of the anti-periodic solution for delayed Cohen-Grossberg neural networks with impulsive effects. First, based on the Lyapunov functional theory and by applying inequality technique, we give some new and useful sufficient conditions to ensure existence and exponential stability of the anti-periodic solutions. Then, we present an example with numerical simulations to illustrate our results. (C) 2014 Published by Elsevier B.V.
引用
收藏
页码：22 / 28
页数：7
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