Exponential p-stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays

被引：64
作者：
Wang, Xiaohu [1 ]
Guo, Qingyi [1 ,2 ]
Xu, Daoyi [1 ]
机构：
[1] Sichuan Univ, Yangtze Ctr Math, Chengdu 610064, Peoples R China
[2] Kangding Nationality Teachers Coll, Dept Math, Kangding 626001, Peoples R China
来源：
MATHEMATICS AND COMPUTERS IN SIMULATION | 2009年 / 79卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Exponential p-stability; Impulsive; Stochastic; Mixed delays; L-operator inequality; ASYMPTOTIC STABILITY; DYNAMIC-ANALYSIS;
D O I：
10.1016/j.matcom.2008.08.008
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, we study the impulsive stochastic Cohen-Grossberg neural networks with mixed delays. By establishing an L-operator differential inequality with mixed delays and using the properties of M-cone and stochastic analysis technique, we obtain some sufficient conditions ensuring the exponential p-stability of the impulsive stochastic Cohen-Grossberg neural networks with mixed delays. These results generalize a few previous known results and remove some restrictions on the neural networks. Two examples are also discussed to illustrate the efficiency of the obtained results. (C) 2008 IMACS. Published by Elsevier B.V. All rights reserved.
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页码：1698 / 1710
页数：13
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