Novel robust stability criteria for a class of neural networks with mixed time-varying delays and nonlinear perturbations

被引：0

作者：

Liu G. ^{[1
]}

Yang S.X. ^{[2
]}

Chai Y. ^{[3
]}

Fu W. ^{[1
]}

机构：

[1] College of Automation, Chongqing University

[2] School of Engineering, University of Guelph, Guelph

[3] State Key Lab. of Power Transmission Equipment and System Security and New Technology of Engineering, Chongqing University

来源：

Information Technology Journal | 2011年 / 10卷 / 11期

关键词：

Linear matrix inequality (LMI); Neural networks; Nonlinear perturbations; Norm-bounded uncertainty; Robust stability; Time-varying delays;

D O I：

10.3923/itj.2011.2202.2207

中图分类号：

学科分类号：

摘要：

The problem of robust stability for a class of neural networks with mixed time-varying delays and nonlinear perturbations is investigated. The mixed delays contain discrete and neutral-type time-varying delays. By constructing a general form of Lyapunov-Krasovskii functional, using some free-weighting matrices, two delay-dependent stability criteria are derived. In particular, the proposed stability conditions are presented in terms of LMI which can be easily solved by some standard numerical packages. In addition, the nonlinear perturbations (or norm-bounded uncertainty) which are more general than those discussed in the previous literature. © 2011 Asian Network for Scientific Information.

引用

页码：2202 / 2207

页数：5

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