Delay-dependent stability analysis for a class of delayed neural networks

被引：0
|
作者：
Wang, RL [1 ]
Liu, YQ
机构：
[1] Guangxi Teachers Univ, Dept Informat Technol, Nanning 530001, Peoples R China
[2] S China Univ Technol, Coll Automat Sci & Engn, Guangzhou 510640, Peoples R China
来源：
ADVANCES IN INTELLIGENT COMPUTING, PT 1, PROCEEDINGS | 2005年 / 3644卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we consider a class of time-delay artificial neural networks and obtain practical criteria to test asymptotic stability of the equilibrium of the time-delay artificial neural networks, with or without perturbations. These criteria require verification of the definiteness of a certain matrix, or verification of a certain inequality. Furthermore, we discuss the exponential stability and estimate the exponential convergence rate for time-delay artificial neural networks. The applicability of our results is demonstrated by means of two specific examples.
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页码：1055 / 1064
页数：10
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