Delay-dependent asymptotic stability for neural networks with distributed delays

被引：38

作者：

Liao, Xiaofeng ^{[1
]}

Liu, Qun

Zhang, Wei

机构：

[1] Chongqing Univ, Dept Comp Sci & Engn, Chongqing 400030, Peoples R China

[2] Chongqing Jiaotong Univ, Sch Comp & Informat, Chongqing 400074, Peoples R China

[3] Chongqing Univ Post & Telecommun, Dept Comp Sci & Technol, Chongqing, Peoples R China

[4] Chongqing Educ Coll, Dept Comp & Modern Educ Technol, Chongqing, Peoples R China

来源：

NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS | 2006年 / 7卷 / 05期

基金：

中国国家自然科学基金;

关键词：

neural networks; distributed delays; Lyapunov functionals; local and global asymptotic stability; EXPONENTIAL STABILITY; BIFURCATION-ANALYSIS; ROBUST STABILITY; 2-NEURON SYSTEM; CRITERIA; MODEL;

D O I：

10.1016/j.nonrwa.2005.11.001

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, dynamical behavior of a class of neural networks with distributed delays is studied by employing suitable Lyapunov functionals, delay-dependent criteria to ensure local and global asymptotic stability of the equilibrium of the neural networks. Our results are applied to classical Hopfield neural networks with distributed delays and some novel asymptotic stability criteria are also derived. The obtained conditions are shown to be less conservative and restrictive than those reported in the known literature. (c) 2005 Elsevier Ltd. All rights reserved.

引用

页码：1178 / 1192

页数：15

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