Stability analysis of fuzzy Markovian jumping Cohen-Grossberg BAM neural networks with mixed time-varying delays

被引：44

作者：

Sathy, R. ^{[1
]}

Balasubramaniam, P. ^{[1
]}

机构：

[1] Deemed Univ, Gandhigram Rural Inst, Dept Math, Gandhigram 624302, Tamil Nadu, India

来源：

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2011年 / 16卷 / 04期

关键词：

Stability; Fuzzy; Markovian jumping; Cohen-Grossberg; Bi directional associative memory; Neural networks; Mixed time varying delays; GLOBAL EXPONENTIAL STABILITY; ROBUST STABILITY; ASYMPTOTIC STABILITY; CRITERIA; SYSTEMS;

D O I：

10.1016/j.cnsns.2010.08.012

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper we investigate the robust stability of uncertain fuzzy Markovian jumping Cohen-Grossberg BAM neural networks with discrete and distributed time varying delays A new delay dependent stability condition is derived under uncertain switching probabilities by Takagi-Sugeno fuzzy model Based on the linear matrix inequality (LMI) technique upper bounds for the discrete and distributed delays are calculated using the LMI toolbox in MATLAB Numerical examples are provided to illustrate the effectiveness of the pro posed method (C) 2010 Elsevier B V All rights reserved

引用

页码：2054 / 2064

页数：11

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