New augmented Lyapunov-Krasovskii functional approach to stability analysis of neural networks with time-varying delays

被引：92

作者：

Kwon, O. M. ^{[1
]}

Park, Ju H. ^{[2
]}

Lee, S. M. ^{[3
]}

Cha, E. J. ^{[4
]}

机构：

[1] Chungbuk Natl Univ, Sch Elect Engn, Cheongju 361763, South Korea

[2] Yeungnam Univ, Nonlinear Dynam Grp, Dept Elect Engn, Kyongsan 712749, South Korea

[3] Daegu Univ, Sch Elect Engn, Gyongsan 712714, South Korea

[4] Chungbuk Natl Univ, Dept Biomed Engn, Sch Med, Cheongju 361763, South Korea

来源：

NONLINEAR DYNAMICS | 2014年 / 76卷 / 01期

基金：

新加坡国家研究基金会;

关键词：

Asymptotic stability; Neural networks; Time-varying delays; Lyapunov method; GLOBAL ROBUST STABILITY; DEPENDENT EXPONENTIAL STABILITY; CRITERIA; DISCRETE; SYSTEMS;

D O I：

10.1007/s11071-013-1122-2

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

This paper is concerned with the problem of stability analysis for neural networks with time-varying delays. By constructing a newly augmented Lyapunov functional and some novel techniques, delay-dependent criteria to guarantee the asymptotic stability of the concerned networks are derived in terms of linear matrix inequalities (LMIs). The improvement of feasible region of the proposed criteria comparing with the previous works is shown by two numerical examples.

引用

页码：221 / 236

页数：16

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