Effects of leakage time-varying delays in Markovian jump neural networks with impulse control

被引：38

作者：

Rakkiyappan, R. ^{[1
]}

Chandrasekar, A. ^{[1
]}

Lakshmanan, S. ^{[2
]}

Park, Ju H. ^{[2
]}

Jung, H. Y. ^{[2
]}

机构：

[1] Bharathiar Univ, Dept Math, Coimbatore 641046, Tamil Nadu, India

[2] Yeungnam Univ, Dept Elect Engn Informat & Commun Engn, Kyongsan 712749, South Korea

来源：

NEUROCOMPUTING | 2013年 / 121卷

基金：

新加坡国家研究基金会;

关键词：

Global exponential stability; Leakage time-varying delays; Lyapunov-Krasovskii functional; Markovian jumping parameters; DEPENDENT EXPONENTIAL STABILITY; NEUTRAL-TYPE; ASYMPTOTIC STABILITY; DISTRIBUTED DELAYS; PARAMETERS; SYNCHRONIZATION; DISCRETE; CRITERIA;

D O I：

10.1016/j.neucom.2013.05.018

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, the stability analysis problem is investigated for delayed neural networks with mixed time-varying delays, impulsive control and Markovian jumping parameters. The mixed time-varying delays include leakage, discrete and distributed time-varying delays. Sufficient conditions for the global exponential stability in the mean square are derived by using Lyapunov-Krasovskii functional having triple integral terms and model transformation technique. The stability criterion that depends on the upper bounds of the leakage time-varying delay and its derivative is given in terms of linear matrix inequalities (LMIs), which can be efficiently solved via standard numerical softwares. Finally, three numerical examples and simulations are given to demonstrate the usefulness and effectiveness of the presented results. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：365 / 378

页数：14

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