New results of global robust exponential stability of neural networks with delays

被引：16

作者：

Zhao, Weirui ^{[1
]}

Zhu, Qing ^{[1
]}

机构：

[1] Wuhan Univ Technol, Dept Math, Wuhan 430070, Peoples R China

来源：

NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS | 2010年 / 11卷 / 02期

关键词：

Neural networks; Delays; Global robust stability; LMI-BASED CRITERIA; CONSTANT;

D O I：

10.1016/j.nonrwa.2009.01.008

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, the global robust exponential stability of interval neural networks with delays is investigated. Employing homeomorphism techniques and Lyapunov functions, we establish some sufficient conditions for the existence, uniqueness, and global robust exponential stability of the equilibrium point for delayed neural networks. It is shown that the obtained results improve and generalize the previously published results. (C) 2009 Elsevier Ltd. All rights reserved.

引用

页码：1190 / 1197

页数：8

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