Global robust exponential stability analysis for stochastic interval neural networks with time-varying delays

被引:17
|
作者
Su, Weiwei [1 ]
Chen, Yiming [1 ]
机构
[1] Yanshan Univ, Coll Sci, Qinhuangdao 066004, Hebei, Peoples R China
关键词
Stochastic interval neural networks; Global robust exponential stability; Time-varying delays; CRITERION; DISCRETE;
D O I
10.1016/j.cnsns.2008.05.001
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, the global exponential stability is investigated for a class of stochastic interval neural networks with time-varying delays. The parameter uncertainties are assumed to be bounded in given compact sets. Based on Lyapunov stable theory and stochastic analysis approaches, the delay-dependent criteria are derived to ensure the global, robust, exponential stability of the addressed system in the mean square. The criteria can be checked easily by the LMI control toolbox in Matlab. A numerical example is given to illustrate the effectiveness and improvement over some existing results. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:2293 / 2300
页数:8
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