Adaptive exponential synchronization in mean square for Markovian jumping neutral-type coupled neural networks with time-varying delays by pinning control

被引：26

作者：

Dai, Anding ^{[1
]}

Zhou, Wuneng ^{[2
]}

Xu, Yuhua ^{[3
]}

Xiao, Cuie ^{[1
]}

机构：

[1] Hunan City Univ, Sch Math & Comp Sci, Yiyang 413000, Hunan, Peoples R China

[2] Donghua Univ, Coll Informat Sci & Technol, Shanghai 201620, Peoples R China

[3] Yunyang Teachers Coll, Dept Math & Finance, Shiyan 442000, Hubei, Peoples R China

来源：

NEUROCOMPUTING | 2016年 / 173卷

关键词：

Synchronization; Neutral-type; Neural networks; Markovian switching; Adaptive pinning control; COMPLEX NETWORKS; DYNAMICAL NETWORKS; STABILITY ANALYSIS;

D O I：

10.1016/j.neucom.2015.08.034

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 adaptive exponential synchronization problem of neutral-type coupled neural networks with Markovian switching parameters is investigated. The switching parameters are modeled as a continuous time, finite state Markov chain. Based on Lyapunov stability theory, stochastic analysis and matrix theory, some sufficient conditions for exponential synchronization in mean square are derived. The adaptive controllers are added to part of nodes, and the adaptive laws are depend on Markov chain and error states. Two numerical examples are exhibited to illustrate the validity of the theoretical results. Through the comparison of average value of synchronization control cost and synchronization time, we verify that control different nodes may be more effectively to achieve synchronization than control fixed nodes when the network topology is switching by a Markov chain. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：809 / 818

页数：10

共 38 条

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