New results for global stability of a class of neutral-type neural systems with time delays

被引：85

作者：

Samli, Ruya ^{[1
]}

Arik, Sabri ^{[1
]}

机构：

[1] Istanbul Univ, Fac Engn, Dept Comp Engn, TR-34320 Istanbul, Turkey

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2009年 / 210卷 / 02期

关键词：

Stability analysis; Neutral-type neural networks; Time delay systems; Lyapunov functionals; EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; VARYING DELAYS; NETWORKS; CRITERIA; DESIGN;

D O I：

10.1016/j.amc.2009.01.031

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper studies the global convergence properties of a class of neutral-type neural networks with discrete time delays. This class of neutral systems includes Cohen-Grossberg neural networks, Hopfield neural networks and cellular neural networks. Based on the Lyapunov stability theorems, some delay independent sufficient conditions for the global asymptotic stability of the equilibrium point for this class of neutral-type systems are derived. It is shown that the results presented in this paper for neutral-type delayed neural networks are the generalization of a recently reported stability result. A numerical example is also given to demonstrate the applicability of our proposed stability criteria. (C) 2009 Elsevier Inc. All rights reserved.

引用

页码：564 / 570

页数：7

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