New delay-dependent global robust passivity analysis for stochastic neural networks with Markovian jumping parameters and interval time-varying delays

被引：5

作者：

Chen, Guoliang ^{[1
]}

Xia, Jianwei ^{[1
]}

Park, Ju H. ^{[2
]}

Zhuang, Guangming ^{[1
]}

机构：

[1] Liaocheng Univ, Sch Math Sci, Liaocheng 252000, Peoples R China

[2] Yeungnam Univ, Dept Elect Engn, 280 Daehak Ro, Kyongsan 712749, South Korea

来源：

COMPLEXITY | 2016年 / 21卷 / 06期

基金：

中国国家自然科学基金; 新加坡国家研究基金会;

关键词：

stochastic neural networks; passivity; interval time-varying delays; Markovian jumping parameters; STABILITY ANALYSIS; EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; DISTRIBUTED DELAYS; NEUTRAL-TYPE; CRITERIA; DISCRETE; SYNCHRONIZATION; SYSTEMS;

D O I：

10.1002/cplx.21677

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

The problem of passivity analysis for stochastic neural networks with Markovian jumping parameters and interval time-varying delays is investigated in this article. By constructing a novel Lyapunov-Krasovskii functional based on the complete delay-decomposing idea and using improved free-weighting matrix method, some improved delay-dependent passivity criteria are established in terms of linear matrix inequalities. Numerical examples are also given to show the effectiveness of the proposed methods. (c) 2015 Wiley Periodicals, Inc. Complexity 21: 167-179, 2016

引用

页码：167 / 179

页数：13

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