Novel Robust Stability Criteria For Uncertain Stochastic Neural Networks with Time-Varying Delay

被引：0
|
作者：
Yonggang Chen
Yunrui Guo
Wenlin Li
机构：
[1] Henan Institute of Science and Technology,Department of Mathematics
[2] Henan Normal University,College of Mathematics and Information Science
来源：
International Journal of Computational Intelligence Systems | 2009年 / 2卷
关键词：
robust stability; stochastic neural networks; time-varying delay; linear matrix inequalities;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper considers the robust stability analysis problem for a class of uncertain stochastic neural networks with time-varying delay. Based on the Lyapunov functional method, and by resorting to the new technique for estimating the upper bound of the stochastic derivative of Lyapunov functionals, the novel asymptotic stability criteria are obatined in terms of Linear matrix inequalities (LMIs). Two numerical examples are presented to show the effectiveness and the less conservativeness of the proposed method.
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页码：1 / 9
页数：8
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