Finite-time synchronization of inertial memristive neural networks with time-varying delays via sampled-date control

被引:79
|
作者
Huang, Dasong [1 ]
Jiang, Minghui [1 ]
Jian, Jigui [1 ]
机构
[1] China Three Gorges Univ, Inst Nonlinear Complex Syst, Yichang 443000, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Inertial memristive neural networks; Finite-time synchronization; Sampled-data control; Time-varying delays; STABILITY;
D O I
10.1016/j.neucom.2017.05.075
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 finite-time synchronization issues for inertial memristive neural networks with time varying delay using hybrid feedback controller with sampled-date term are investigated. Firstly, by constructing a proper variable substitution,the original system is transformed into the first order differential system. Next, constructing a useful Lyapunov function, a suitable controller and using inequality techniques, some new testable algebraic criterion are obtained for ensuring the finite-time synchronization goal. Moreover, we discussed deeply on the relation between the parameter and estimated value of settling time in the different cases, and we can obtain the minimum estimated value of settling time. Finally, the effectiveness of the theoretical results have been illustrated via two numerical examples. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:527 / 539
页数:13
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