Global Exponential Stability Analysis for Uncertain Stochastic Neural Networks with Discrete and Distributed Time-Varying Delays

被引：0
|
作者：
Wei, Guan [1 ]
Hui, Zeng [1 ]
机构：
[1] Yanshan Univ, Sch Sci, Qinhuangdao, Peoples R China
来源：
INFORMATION COMPUTING AND APPLICATIONS, PT I | 2011年 / 243卷
关键词：
stochastic neural networks; discrete delays; distributed delay; norm-bounded uncertainties; global exponential stability; blocked matrix method;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the global exponential stability is investigated for a class of stochastic neural networks with both discrete and distributed delays and norm-bounded uncertainties. Based on Lyapunov stability theory and stochastic analysis approaches, delay-dependent criteria are derived to ensure the global, robust, exponential stability of the addressed system in the mean square for all admissible parameter uncertainties. 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.
引用
收藏
页码：284 / 292
页数：9
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