Synchronization schemes for coupled identical Yang-Yang type fuzzy cellular neural networks

被引:70
作者
Xia, Yonghui [1 ]
Yang, Zijiang [2 ]
Han, Maoan [3 ]
机构
[1] Zhejiang Normal Univ, Dept Math, Jinhua 321004, Peoples R China
[2] York Univ, Sch Informat Technol, Toronto, ON M3J 1P3, Canada
[3] Shanghai Normal Univ, Inst Math, Shanghai 200234, Peoples R China
基金
上海市自然科学基金; 加拿大自然科学与工程研究理事会;
关键词
Fuzzy; Neural networks; Synchronization; Delays; TIME-VARYING DELAYS; GLOBAL EXPONENTIAL STABILITY; ALMOST-PERIODIC SOLUTION; ROBUST STABILITY; CHAOTIC SYSTEMS; IMPULSES; PERTURBATION; EXISTENCE; CONSTANT;
D O I
10.1016/j.cnsns.2009.01.028
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper proposes an adaptive procedure to the problem of synchronization for a class of coupled identical Yang-Yang type fuzzy cellular neural networks (YYFCNN) with time-varying delays. Based on the simple adaptive controller, a set of sufficient conditions are developed to guarantee the synchronization of the coupled YYFCNN with time-varying delays. The results are much different from previous ones. It is proved that two coupled identical YYFCNN with time-varying delays can achieve synchronization by enhancing the coupled strength dynamically. In addition, this kind of controller is simple to be implemented and it is fairly robust against the effect of weak noise in the given time series. The approaches are based on using the invariance principle of functional differential equations, constructing a general Lyapunov-Krasovskii functional and employing a linear matrix inequality (LMI). An illustrative example and its simulations show the feasibility of our results. Finally, an application is given to show how to apply the presented synchronization scheme of YYFCNN to secure communication. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:3645 / 3659
页数:15
相关论文
共 34 条
[1]   Global asymptotic stability of a larger class of neural networks with constant time delay [J].
Arik, S .
PHYSICS LETTERS A, 2003, 311 (06) :504-511
[2]   Equilibrium analysis of delayed CNN's [J].
Arik, S ;
Tavsanoglu, V .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS, 1998, 45 (02) :168-171
[3]  
BOYD S, 1994, LINEAR MATRIX INEQUA, P46218
[4]   Adaptive synchronization of neural networks with or without time-varying delay [J].
Cao, JD ;
Lu, JQ .
CHAOS, 2006, 16 (01)
[5]   Global stability conditions for delayed CNNs [J].
Cao, J. .
IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 2001, 48 (11) :1330-1333
[6]   Global exponential stability and periodicity of recurrent neural networks with time delays [J].
Cao, JD ;
Wang, J .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2005, 52 (05) :920-931
[7]   Global synchronization of coupled delayed neural networks and applications to chaotic CNN models [J].
Chen, GR ;
Zhou, J ;
Liu, ZR .
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 2004, 14 (07) :2229-2240
[8]   CELLULAR NEURAL NETWORKS - APPLICATIONS [J].
CHUA, LO ;
YANG, L .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS, 1988, 35 (10) :1273-1290
[9]   Synchronization of delayed fuzzy cellular neural networks based on adaptive control [J].
Ding, Wei ;
Han, Maoan .
PHYSICS LETTERS A, 2008, 372 (26) :4674-4681
[10]  
HALE JK, 1977, THEORY FUNCTIONAL DI, P46218