Exponential synchronization of delayed Markovian jump complex networks with generally uncertain transition rates

被引：15
|
作者：
Xu, Ruiping [1 ,2 ]
Kao, Yonggui [3 ]
Gao, Cunchen [2 ]
机构：
[1] Qingdao Univ, Coll Math, Qingdao 266071, Peoples R China
[2] Ocean Univ China, Coll Informat Sci & Engn, Qingdao 266100, Peoples R China
[3] Harbin Inst Technol, Dept Math, Weihai 264209, Peoples R China
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2015年 / 271卷
关键词：
Exponential synchronization; Markovian jump complex networks; Generally uncertain transition rates; Kronecker product; COUPLED NEURAL-NETWORKS; DYNAMICAL NETWORKS; GLOBAL SYNCHRONIZATION; SYSTEMS; STABILITY; STABILIZATION; ARRAYS;
D O I：
10.1016/j.amc.2015.09.032
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper investigates the exponential synchronization problem for a class of Markovian jump complex networks(MJCNs) with generally uncertain transition rates(GUTRs). In this GUTR neural network model, each transition rate can be completely unknown or only its estimate value is known. This new uncertain model could be applied to many practical cases. Based on the Lyapunov functional method and Kronecker product technique, a sufficient condition on the exponentially synchronization in mean square is derived in terms of linear matrix inequalities (LMIs)-which can be easily solved by using the Matlab LMI toolbox. Finally, one numerical example is well studied to illustrate the effectiveness of the developed method. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码：682 / 693
页数：12
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