Robust Stochastic Stability Analysis for Uncertain Neutral-Type Delayed Neural Networks Driven by Wiener Process

被引：6

作者：

Zhang, Weiwei ^{[2
]}

Wang, Linshan ^{[1
]}

机构：

[1] Ocean Univ China, Dept Math, Qingdao 266100, Peoples R China

[2] Ocean Univ China, Coll Informat Sci & Engn, Qingdao 266100, Peoples R China

来源：

JOURNAL OF APPLIED MATHEMATICS | 2012年

基金：

中国国家自然科学基金;

关键词：

DISTRIBUTED TIME DELAYS; EXPONENTIAL STABILITY; GLOBAL STABILITY; VARYING DELAYS; SYSTEMS; OPTIMIZATION; PARAMETERS; CRITERIA;

D O I：

10.1155/2012/829594

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The robust stochastic stability for a class of uncertain neutral-type delayed neural networks driven by Wiener process is investigated. By utilizing the Lyapunov-Krasovskii functional and inequality technique, some sufficient criteria are presented in terms of linear matrix inequality (LMI) to ensure the stability of the system. A numerical example is given to illustrate the applicability of the result.

引用

页数：12

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