New stability criteria of neural networks with interval time-varying delay: A piecewise delay method

被引：106

作者：

Zhang, Yijun ^{[2
]}

Yue, Dong ^{[1
]}

Tian, Engang ^{[1
]}

机构：

[1] Nanjing Normal Univ, Inst Informat & Control Engn Technol, Nanjing 210042, Peoples R China

[2] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2009年 / 208卷 / 01期

关键词：

Neural networks; Stability; Interval delay; Delay-dependent; LMI; GLOBAL ASYMPTOTIC STABILITY; DEPENDENT EXPONENTIAL STABILITY; ROBUST STABILITY; UNCERTAIN SYSTEMS; LARGER CLASS; LMI APPROACH; DISCRETE;

D O I：

10.1016/j.amc.2008.11.046

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper provides improved conditions for the global asymptotic stability of a class of neural networks with interval time-varying delays. A piecewise delay method is. firstly proposed. In this method, the variation interval of the time delay is divided into two subintervals by introducing its central point. Then, by constructing a new Lyapunov-Krasovskii functional and checking its variation in the two subintervals, respectively, some new delay-dependent stability criteria for the addressed neural networks are derived. Numerical examples are provided to show that the achieved conditions are less conservative than some existing ones in the literature. Crown Copyright (C) 2008 Published by Elsevier Inc. All rights reserved.

引用

页码：249 / 259

页数：11

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