Passivity analysis for neural networks of neutral type with Markovian jumping parameters and time delay in the leakage term

被引：79

作者：

Balasubramaniam, P. ^{[1
]}

Nagamani, G. ^{[1
]}

Rakkiyappan, R. ^{[1
]}

机构：

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

来源：

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2011年 / 16卷 / 11期

关键词：

Linear matrix inequality (LMI); Delayed neural networks; Passivity; Interval time-varying delays; Leakage delay; Lyapunov method; GLOBAL EXPONENTIAL STABILITY; DEPENDENT STABILITY; DISCRETE; SYNCHRONIZATION; SYSTEMS;

D O I：

10.1016/j.cnsns.2011.03.028

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, the problem of passivity analysis is investigated for neutral type neural networks with Markovian jumping parameters and time delay in the leakage term. The delay is 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. By constructing proper Lyapunov-Krasovskii functional, new delay-dependent passivity conditions are derived in terms of linear matrix inequalities (LMIs). Moreover, it is well known that the passivity behavior of neural networks is very sensitive to the time delay in the leakage term. Finally, three numerical examples are given to show the effectiveness and less conservatism of the proposed method. (C) 2011 Elsevier B.V. All rights reserved.

引用

页码：4422 / 4437

页数：16

共 47 条

[1] An analysis of exponential stability of delayed neural networks with time varying delays
Arik, S
[J]. NEURAL NETWORKS, 2004, 17 (07) : 1027 - 1031
[2] Delay-dependent robust stability analysis for Markovian jumping stochastic Cohen-Grossberg neural networks with discrete interval and distributed time-varying delays
Balasubramaniam, P.
Rakkiyappan, R.
[J]. NONLINEAR ANALYSIS-HYBRID SYSTEMS, 2009, 3 (03) : 207 - 214
[3] Boyd S, 1994, LINEAR MATRIX INEQUA, V15
[4] Passivity approach to fuzzy control systems
Calcev, G
Gorez, R
De Neyer, M
[J]. AUTOMATICA, 1998, 34 (03) : 339 - 344
[5] Global asymptotical stability of recurrent neural networks with multiple discrete delays and distributed delays
Cao, Jinde
Yuan, Kun
Li, Han-Xiong
[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2006, 17 (06): : 1646 - 1651
[6] Passivity analysis for uncertain neural networks with discrete and distributed time-varying delays
Chen, Bing
Li, Hongyi
Lin, Chong
Zhou, Qi
[J]. PHYSICS LETTERS A, 2009, 373 (14) : 1242 - 1248
[7] Improved Delay-Dependent Asymptotic Stability Criteria for Delayed Neural Networks
Chen, Wu-Hua
Zheng, Wei Xing
[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2008, 19 (12): : 2154 - 2161
[8] Improved Results on Passivity Analysis of Uncertain Neural Networks with Time-Varying Discrete and Distributed Delays
Chen, Yonggang
Li, Wenlin
Bi, Weiping
[J]. NEURAL PROCESSING LETTERS, 2009, 30 (02) : 155 - 169
[9] Passivity analysis of stochastic time-delay neural networks
Chen, Yun
Wang, Huijiao
Xue, Anke
Lu, Renquan
[J]. NONLINEAR DYNAMICS, 2010, 61 (1-2) : 71 - 82
[10] Passivity and complexity
Chua, LO
[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS, 1999, 46 (01): : 71 - 82

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