An analysis on global robust exponential stability of neural networks with time-varying delays

被引：10
|
作者：
Shao, Jin-Liang [1 ]
Huang, Ting-Zhu [1 ]
Zhou, Sheng [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Appl Math, Chengdu 610054, Sichuan, Peoples R China
来源：
NEUROCOMPUTING | 2009年 / 72卷 / 7-9期
关键词：
Interval neural networks; Time-varying delays; Global robust exponential stability; M-matrix; VARIABLE DELAYS; ASYMPTOTIC STABILITY; CRITERIA;
D O I：
10.1016/j.neucom.2008.11.023
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper presents a new sufficient condition for the existence, uniqueness and global robust exponential stability of the equilibrium point for interval neural networks with time-varying delays. Theoretical analysis indicates that the obtained result improves and generalizes some previous results derived in the literatures. It is also shown by a numerical example that a recently reported result is invalid because the proof of it is not always right. Finally, a numerical example and the corresponding simulation are given to show the effectiveness of the obtained result. (c) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码：1993 / 1998
页数：6
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