Stability analysis for neural networks with time-varying delay: A more general delay decomposition approach

被引：18

作者：

Chen, Yonggang ^{[1
]}

Bi, Weiping ^{[2
]}

Li, Wenlin ^{[2
]}

机构：

[1] Henan Inst Sci & Technol, Dept Math, Xinxiang 453003, Peoples R China

[2] Henan Normal Univ, Coll Math & Informat Sci, Xinxiang 453007, Peoples R China

来源：

NEUROCOMPUTING | 2010年 / 73卷 / 4-6期

关键词：

Stability analysis; Neural networks; Time-varying delay; Delay decomposition approach; Linear matrix inequalities (LMIs); GLOBAL ASYMPTOTIC STABILITY; ROBUST STABILITY; CRITERIA; SYSTEMS; UNCERTAINTIES;

D O I：

10.1016/j.neucom.2009.10.005

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 considers the stability analysis problem for neural networks with time-varying delay. Firstly, the new augmented Lyapunov functional is constructed by employing the more general decomposition approach. Then based on the Lyapunov stability theory and free weight matrix method, the novel delay-dependent stability condition is derived in terms of linear matrix inequalities (LMIs). Numerical examples show that the proposed method is more effective than some existing ones. (C) 2009 Elsevier B.V. All rights reserved.

引用

页码：853 / 857

页数：5

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