New results of robust stability analysis for neutral-type neural networks with time-varying delays and Markovian jumping parameters

被引：23
|
作者：
Lakshmanan, S. [1 ]
Balasubramaniam, P. [1 ]
机构：
[1] Deemed Univ, Dept Math, Gandhigram Rural Inst, Gandhigram 624302, Tamil Nadu, India
来源：
CANADIAN JOURNAL OF PHYSICS | 2011年 / 89卷 / 08期
关键词：
GLOBAL ASYMPTOTIC STABILITY; EXPONENTIAL STABILITY; STOCHASTIC STABILITY; DEPENDENT STABILITY; DISTRIBUTED DELAYS; CRITERIA; SYSTEMS;
D O I：
10.1139/P11-059
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
In this paper, robust stability analysis for neutral-type neural networks with time-varying delays and Markovian jumping parameters is conducted. By using the delay-decomposition approach, a new Lyapunov-Krasovskii functional is constructed. Based on this Lyapunov-Krasovskii functional and some stochastic stability theory, delay-dependent stability criteria are obtained in terms of linear matrix inequalities. Finally, three numerical examples are given to illustrate the effectiveness and reduced conservatism of our theoretical results.
引用
收藏
页码：827 / 840
页数：14
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