Robust exponential stability of Markovian jumping neural networks with mode-dependent delay

被引：27
|
作者：
Han, Wei [1 ]
Liu, Yan [2 ]
Wang, Linshan [3 ]
机构：
[1] N Univ China, Dept Math, Taiyuan 030051, Shanxi, Peoples R China
[2] Hebei Normal Univ Sci & Technol, Dept Math & Phys, Qinhuangdao 066004, Hebei, Peoples R China
[3] Ocean Univ China, Dept Math, Qingdao 266071, Peoples R China
来源：
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2010年 / 15卷 / 09期
基金：
中国国家自然科学基金;
关键词：
Markovian jumping neural networks; Robust exponential stability; Mode-dependent delay; Linear matrix inequality; TIME-VARYING DELAYS; ASYMPTOTIC STABILITY; DISTRIBUTED DELAYS; GLOBAL STABILITY; CRITERION; PARAMETERS; DISCRETE;
D O I：
10.1016/j.cnsns.2009.09.024
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper deals with the robust exponential stability problem for a class of Markovian jumping neural networks with time delay. The delay considered varies randomly, depending on the mode of the networks. By using a new Lyapunov-Krasovskii functional, a delay-dependent stability criterion is presented, which can be expressed in terms of linear matrix inequalities (LMIs). A numerical example is given to show the effectiveness of the results. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码：2529 / 2535
页数：7
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