Improved delay-dependent exponential stability for uncertain stochastic neural networks with time-varying delays

被引：67

作者：

Kwon, O. M. ^{[3
]}

Lee, S. M. ^{[2
]}

Park, Ju H. ^{[1
]}

机构：

[1] Yeungnam Univ, Dept Elect Engn, Kyongsan 712749, South Korea

[2] Daegu Univ, Sch Elect Engn, Kyongsan, South Korea

[3] Chungbuk Natl Univ, Sch Elect Engn, Cheongju, South Korea

来源：

PHYSICS LETTERS A | 2010年 / 374卷 / 10期

关键词：

Stochastic neural networks; Time-varying delays; LMI; Lyapunov method; GLOBAL ASYMPTOTIC STABILITY; ROBUST STABILITY; MEAN-SQUARE;

D O I：

10.1016/j.physleta.2010.01.007

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

This Letter investigates the problem of delay-dependent exponential stability analysis for uncertain stochastic neural networks with time-varying delay. Based on the Lyapunov stability theory, improved delay-dependent exponential stability criteria for the networks are established in terms of linear matrix inequalities (LMIs). (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：1232 / 1241

页数：10

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