An improved global exponential stability criterion for delayed neural networks

被引：8

作者：

Liu, Kaiyu ^{[1
]}

Zhang, Hongqiang ^{[2
]}

机构：

[1] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China

[2] Changsha Univ Sci & Technol, Coll Math & Comput Sci, Changsha 410076, Hunan, Peoples R China

来源：

NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS | 2009年 / 10卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Global exponential stability; Neural networks; Linear matrix inequality; Halanay inequality; Bellman inequality; TIME-VARYING DELAYS; ASYMPTOTIC STABILITY; DYNAMICS;

D O I：

10.1016/j.nonrwa.2008.04.011

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Based on Lyapunov-Krasovskii stability theory and the linear matrix inequality (LMI) technique, a criterion is derived to guarantee the global exponential stability of the class of delayed neural networks with time-varying delays, which generalizes and improves previous results. Numerical examples demonstrate the effectiveness of the criterion. (c) 2008 Elsevier Ltd. All rights reserved.

引用

页码：2613 / 2619

页数：7

共 14 条

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