Improved Stability Criteria for Discrete-Time Stochastic Neural Networks with Randomly Time-Varying Delays

被引：0
|
作者：
Luo, Mengzhuo [1 ]
Zhong, Shouming [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Peoples R China
来源：
BIO-INSPIRED COMPUTING AND APPLICATIONS | 2012年 / 6840卷
关键词：
Delay-dependent stability; Neural networks; Time-varying delay; Linear matrix inequality(LMI); Free-weighting matrix; ROBUST STABILITY;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper investigates the problem of exponential stability for a class of discrete-time stochastic neural network with randomly time-varying delays. Compared with some previous results, the new conditions obtained in this paper are less conservative. Finally, a numerical example is exploited to show the usefulness of the results derived.
引用
收藏
页码：8 / 13
页数：6
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