STABILITY OF IMPULSIVE HOPFIELD NEURAL NETWORKS WITH MARKOVIAN SWITCHING AND TIME-VARYING DELAYS

被引：24
|
作者：
Raja, Ramachandran [2 ]
Sakthivel, Rathinasamy [1 ]
Anthoni, Selvaraj Marshal [3 ]
Kim, Hyunsoo [1 ]
机构：
[1] Sungkyunkwan Univ, Dept Math, Suwon 440746, South Korea
[2] Periyar Univ, Dept Math, Salem 636011, India
[3] Anna Univ Technol, Dept Math, Coimbatore 641047, Tamil Nadu, India
来源：
INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE | 2011年 / 21卷 / 01期
关键词：
Hopfield neural networks; Markovian jumping; stochastic stability; Lyapunov function; impulses; EXPONENTIAL STABILITY; ROBUST STABILITY; STOCHASTIC STABILITY; JUMPING PARAMETERS; INTERVAL; SYSTEMS; STABILIZATION;
D O I：
10.2478/v10006-011-0009-y
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper is concerned with stability analysis for a class of impulsive Hopfield neural networks with Markovian jumping parameters and time-varying delays. The jumping parameters considered here are generated from a continuous-time discrete-state homogenous Markov process. By employing a Lyapunov functional approach, new delay-dependent stochastic stability criteria are obtained in terms of linear matrix inequalities (LMIs). The proposed criteria can be easily checked by using some standard numerical packages such as theMatlab LMI Toolbox. A numerical example is provided to show that the proposed results significantly improve the allowable upper bounds of delays over some results existing in the literature.
引用
收藏
页码：127 / 135
页数：9
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