New stability criteria for neutral-type Cohen-Grossberg neural networks with discrete and distributed delays

被引：5

作者：

Zheng, Cheng-De ^{[1
]}

Li, Jing-Wen ^{[1
]}

Wang, Zhanshan ^{[2
]}

机构：

[1] Dalian Jiaotong Univ, Sch Sci, Dalian 116028, Peoples R China

[2] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110004, Peoples R China

来源：

INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS | 2012年 / 89卷 / 04期

基金：

中国博士后科学基金; 中国国家自然科学基金; 高等学校博士学科点专项科研基金;

关键词：

global robust stability; neutral-type; Jensen integral inequality; free-weighting matrix; Cohen-Grossberg neural networks; homeomorphism mapping; GLOBAL ASYMPTOTIC STABILITY; DEPENDENT EXPONENTIAL STABILITY; ROBUST STABILITY; OPTIMIZATION; INTERVAL;

D O I：

10.1080/00207160.2011.642298

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper studies the existence, uniqueness and globally robust exponential stability for a class of uncertain neutral-type Cohen-Grossberg neural networks with time-varying and unbounded distributed delays. Based on Lyapunov-Krasovskii functional, by involving a free-weighting matrix, using the homeomorphism mapping principle, Cauchy-Schwarz inequality, Jensen integral inequality, linear matrix inequality techniques and matrix decomposition method, several delay-dependent and delay-independent sufficient conditions are obtained for the robust exponential stability of considered neural networks. Two numerical examples are given to show the effectiveness of our results.

引用

页码：443 / 466

页数：24

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