Global exponential robust stability of static interval neural networks with S-type distributed delays

被引：35

作者：

Han, Wei ^{[1
]}

Kao, Yonggui ^{[2
]}

Wang, Linshan ^{[3
]}

机构：

[1] N Univ China, Dept Math, Taiyuan 030051, Shanxi, Peoples R China

[2] Harbin Inst Technol, Dept Math, Weihai 264209, Shandong, Peoples R China

[3] Ocean Univ China, Dept Math, Qingdao 266071, Shandong, Peoples R China

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2011年 / 348卷 / 08期

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

ASYMPTOTIC STABILITY; TIME DELAYS; BOUND CONSTRAINTS; SYSTEMS; OPTIMIZATION; DISCRETE; CRITERIA; MODELS;

D O I：

10.1016/j.jfranklin.2011.05.023

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The authors in [7] obtained the global asymptotical stability for static interval neural networks with S-type distributed delays by using the Razumikhin theorem. The aim of our paper is to investigate the global exponential robust stability by using the Lyapunov functional methods, and we will improve the proof methods more concise. A theorem and a corollary were obtained in which the boundedness, monotonicity and differentiability conditions on the activation functions are not required. So we generalize the results of related literature [7]. As an application, an example to demonstrate our results is given. (C) 2011 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：2072 / 2081

页数：10

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