Mean square exponential stability and periodic solutions of stochastic interval neural networks with mixed time delays

被引：7

作者：

Wang, Fen ^{[1
,2
]}

Wu, Huaiyu ^{[1
]}

机构：

[1] Wuhan Univ Sci & Technol, Coll Informat Sci & Engn, Wuhan 430081, Peoples R China

[2] Wuhan Univ Sci & Technol, Coll Sci, Wuhan 430081, Peoples R China

来源：

NEUROCOMPUTING | 2010年 / 73卷 / 16-18期

基金：

中国国家自然科学基金;

关键词：

Neural networks; Lyapunov functional; Mean square exponential stability; Periodic solutions; GLOBAL ASYMPTOTIC STABILITY; ROBUST STABILITY; DISCRETE; EXISTENCE;

D O I：

10.1016/j.neucom.2010.04.020

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper concerns with the existence and the mean square exponential stability of periodic solutions of stochastic interval neural networks with mixed time delays. By applying Lyapunov functional, inequality technique, Ito.s differential formula and fixed point theorem, the criteria are derived in terms of linear matrix inequalities. Three numerical examples are provided to illustrate the effectiveness of the proposed solutions. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：3256 / 3263

页数：8

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