Finite-time synchronization of memristive neural networks with time-varying delays via two control methods

被引：8

作者：

Li, Xiaofan ^{[1
]}

Fang, Jian-an ^{[2
]}

Li, Huiyuan ^{[2
]}

机构：

[1] Yancheng Inst Technol, Sch Elect Engn, Yancheng 224051, Peoples R China

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

来源：

MATHEMATICAL METHODS IN THE APPLIED SCIENCES | 2019年 / 42卷 / 08期

关键词：

discontinuous adaptive control; discontinuous control; finite-time synchronization; memristive neural networks; time-varying delays; EXPONENTIAL STABILIZATION; DYNAMICAL NETWORKS; COMPLEX NETWORKS; MIXED DELAYS; STABILITY; DISCRETE;

D O I：

10.1002/mma.5547

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, on the basis of the Lyapunov stability theory and finite-time stability lemma, the finite-time synchronization problem for memristive neural networks with time-varying delays is studied by two control methods. First, the discontinuous state-feedback control rule containing integral part for square sum of the synchronization error and the discontinuous adaptive control rule are designed for realizing synchronization of drive-response memristive neural networks in finite time, respectively. Then, by using some important inequalities and defining suitable Lyapunov functions, some algebraic sufficient criteria guaranteeing finite-time synchronization are deduced for drive-response memristive neural networks in finite time. Furthermore, we give the estimation of the upper bounds of the settling time of finite-time synchronization. Lastly, the effectiveness of the obtained sufficient criteria guaranteeing finite-time synchronization is validated by simulation.

引用

页码：2746 / 2760

页数：15

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