New delay-dependent stability criteria for uncertain stochastic neural networks with discrete interval and distributed delays

被引：18

作者：

Chen, Huabin ^{[1
]}

机构：

[1] Nanchang Univ, Dept Math, Nanchang 330031, Jiangxi, Peoples R China

来源：

NEUROCOMPUTING | 2013年 / 101卷

关键词：

Uncertain stochastic neural networks; Lyapunov-Krasovskii functional; Linear matrix inequalities (LMIs); Interval time-varying delay; Distributed delay; SQUARE EXPONENTIAL STABILITY; ROBUST STABILITY; MEAN-SQUARE; GLOBAL STABILITY;

D O I：

10.1016/j.neucom.2012.06.010

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 studies the globally robustly asymptotical stability in mean square of uncertain stochastic neural networks with discrete interval and distributed time-varying delays. By constructing an augmented Lyapunov-Krasovskii functional, some delay-dependent criteria for the globally robustly asymptotical stability of such systems are formulated in terms of linear matrix inequalities (LMIs). Finally, two numerical examples are provided to illustrate the effectiveness of the obtained results. (C) 2012 Elsevier B.V. All rights reserved.

引用

页码：1 / 9

页数：9

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