Delay-range dependent stability criteria for neural networks with Markovian jumping parameters

被引：48

作者：

Balasubramaniam, P. ^{[1
]}

Lakshmanan, S. ^{[1
]}

机构：

[1] Gandhigram Rural Univ, Dept Math, Gandhigram 624302, Tamilnadu, India

来源：

NONLINEAR ANALYSIS-HYBRID SYSTEMS | 2009年 / 3卷 / 04期

关键词：

Delay/interval-dependent stability; Linear matrix inequality; Lyapunov-Krasovskii functional; Markovian jumping parameters; Hopfield neural networks; GLOBAL ASYMPTOTIC STABILITY; EXPONENTIAL STABILITY; ROBUST STABILITY; SYSTEMS;

D O I：

10.1016/j.nahs.2009.06.012

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 a stability analysis problem for neural networks with Markovian jumping parameters. The jumping parameters considered here are generated from a continuous-time discrete-state homogenous Markov process, which are governed by a Markov process with discrete and finite state space. A new type of Markovian jumping matrix 131 is introduced in this paper. The discrete delays are assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. Based on the new Lyapunov-Krasovskii functional, delay-interval dependent stability criteria are obtained in terms of linear matrix inequalities (LMIs). Finally, a numerical example is provided to demonstrate the lower conservatism and the effectiveness of the proposed LMI conditions. (C) 2009 Elsevier Ltd. All rights reserved.

引用

页码：749 / 756

页数：8

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