A global exponential robust stability criterion for interval delayed neural networks with variable delays

被引：28

作者：

Li, CD ^{[1
]}

Liao, XF

Zhang, R

机构：

[1] Chongqing Univ, Coll Comp Sci, Chongqing 400030, Peoples R China

[2] Chongqing Univ, Coll Econ & Business Adm, Chongqing 400030, Peoples R China

来源：

NEUROCOMPUTING | 2006年 / 69卷 / 7-9期

基金：

中国国家自然科学基金;

关键词：

interval delayed neural networks (IDNN); exponential robust stability; variable delay; Lyapunov-Krasovskii functional; linear matrix; inequality (LMI);

D O I：

10.1016/j.neucom.2005.04.009

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The issue of exponential robust stability for interval delayed neural networks with variable delays is studied. An approach combining the Lyapunov-Krasovskii functional with the differential inequality and linear matrix inequality techniques is taken to investigate this problem. The proposed criterion for exponential stability generalizes and improves those reported recently in the literature. Two numerical examples are also presented to illustrate our results. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：803 / 809

页数：7

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