Delay-dependent stability of neutral type neural networks with distributed delays

被引：71
|
作者：
Feng, Jun-e [1 ,2 ]
Xu, Shengyuan [1 ]
Zou, Yun [1 ]
机构：
[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Peoples R China
[2] Shandong Univ, Sch Math & Syst Sci, Jinan 250100, Peoples R China
来源：
NEUROCOMPUTING | 2009年 / 72卷 / 10-12期
关键词：
Delay-dependent conditions; Discrete delays; Distributed delays; Global asymptotic stability; Linear matrix inequality; Neural networks; GLOBAL ROBUST STABILITY; EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; DISCRETE; CRITERION;
D O I：
10.1016/j.neucom.2008.10.018
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper deals with the problem of stability analysis of neutral type neural networks with both discrete and unbounded distributed delays. In terms of linear matrix inequalities, delay-dependent conditions are obtained, which guarantee the considered delayed neural network to have a unique equilibrium point, which is globally asymptotically stable. Numerical examples are given to show the less conservatism and effectiveness of the proposed stability conditions. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码：2576 / 2580
页数：5
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