Exponential synchronization for inertial coupled neural networks under directed topology via pinning impulsive control

被引：27
|
作者：
Chen, Shanshan [1 ]
Jiang, Haijun [1 ]
Lu, Binglong [1 ]
Yu, Zhiyong [1 ]
机构：
[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Peoples R China
来源：
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2020年 / 357卷 / 03期
关键词：
TIME-VARYING DELAY; DYNAMICAL NETWORKS; CRITERIA; STABILITY; STABILIZATION; SYSTEMS; MODEL;
D O I：
10.1016/j.jfranklin.2019.11.032
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This article focuses on the exponential synchronization of inertial coupled neural networks (ICNNs) with time-varying delays. An extended Halanay differential inequality, matrix decomposition theory and the average impulsive interval approach are used to derive some sufficient conditions. Furthermore, in the view of directed topology, the pinning impulsive control is designed so that the dynamical networks can achieve the exponential synchronization. Finally, some numerical examples are given to illustrate our theoretical results. (C) 2019 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：1671 / 1689
页数：19
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