Existence and global exponential stability of equilibrium of competitive neural networks with different time scales and multiple delays

被引：56

作者：

Gu, Haibo ^{[2
]}

Jiang, Haijun ^{[1
]}

Teng, Zhidong ^{[1
]}

机构：

[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Peoples R China

[2] Xinjiang Normal Univ, Coll Math Sci, Urumqi 830054, Peoples R China

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2010年 / 347卷 / 05期

关键词：

Competitive neural networks; Equilibrium point; Time scale; Global exponential stability; VARYING DELAYS; ASYMPTOTIC STABILITY; DISTRIBUTED DELAYS; DYNAMICS;

D O I：

10.1016/j.jfranklin.2009.03.005

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, some sufficient conditions are obtained for existence and global exponential stability of a unique equilibrium point of competitive neural networks with different time scales and multiple delays by using nonlinear Lipschitz measure (NLM) method and constructing suitable Lyapunov functional. The results of this paper are new and they complete previously known results. (C) 2010 Published by Elsevier Ltd. on behalf of The Franklin Institute.

引用

页码：719 / 731

页数：13

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