New stability criteria for neural networks with time-varying delays

被引：18

作者：

Hua, Changchun ^{[1
]}

Yang, Xian ^{[1
]}

Yan, Jing ^{[1
]}

Guan, Xinping ^{[1
]}

机构：

[1] Yanshan Univ, Inst Elect Engn, Qinhuangdao 066004, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2012年 / 218卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Neural network; Time-varying delay; Stability; Linear matrix inequality; GLOBAL ASYMPTOTIC STABILITY; EXPONENTIAL STABILITY; NEUTRAL-TYPE; SYSTEMS; STABILIZATION; STATE;

D O I：

10.1016/j.amc.2011.10.070

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper is concerned with the stability analysis problem of neural networks with time delays. The delay intervals [-d(t),0] and [-h,0] are divided into m subintervals with equal length. Some free matrices are introduced to build the relationship among the elements of the resultant matrix inequalities. With the above operations, the new stability criteria are built for the general class of neural networks. The conditions are presented in the form of linear matrix inequalities (LMIs), which can be solved by the numerically efficient Matlab LMI toolbox. Several examples are provided to show that our methods are much less conservative than recently reported ones. (C) 2011 Elsevier Inc. All rights reserved.

引用

页码：5035 / 5042

页数：8

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