Exponential synchronization of chaotic neural networks with time-varying delay via intermittent output feedback approach

被引:23
作者
Zhang, Zhi-Ming [1 ]
He, Yong [2 ,3 ]
Wu, Min [2 ,3 ]
Wang, Qing-Guo [4 ]
机构
[1] Cent S Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China
[2] China Univ Geosci, Sch Automat, Wuhan 430074, Hubei, Peoples R China
[3] Hubei Key Lab Adv Control & Intelligent Automat C, Wuhan 430074, Hubei, Peoples R China
[4] Univ Johannesburg, Inst Intelligent Syst, Johannesburg, South Africa
基金
中国国家自然科学基金;
关键词
Exponential synchronization; Neural networks; Time-varying delay; Lyapunov-Krasovskii functional; Intermittent output feedback control; GLOBAL ASYMPTOTIC STABILITY; SAMPLED-DATA; LURE SYSTEMS; H-INFINITY; NONLINEAR-SYSTEMS; COMPLEX NETWORKS; MIXED DELAYS; STABILIZATION; CRITERIA; DISCRETE;
D O I
10.1016/j.amc.2017.07.019
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper is dealt with the problem of exponential synchronization for chaotic neural networks with time-varying delay by using intermittent output feedback control. Based on the Lyapunov-Krasovskii functional method and the lower bound lemma for reciprocally convex technique, a novel criterion for existence of the controller is first established to ensure synchronization between the master and slave systems. Moreover, from the delay point of view, the derived criterion is extended to the relaxed case because of introducing an adjustable parameter in the Lyapunov-Krasovskii functional. Finally, a numerical simulation is carried out to demonstrate the effectiveness of the proposed synchronization law. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:121 / 132
页数:12
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