Finite-time synchronization of switched neural networks with state-dependent switching via intermittent control

被引：29

作者：

Wu, Yongbao ^{[1
]}

Gao, Yixuan ^{[1
]}

Li, Wenxue ^{[1
]}

机构：

[1] Harbin Inst Technol Weihai, Dept Math, Weihai 264209, Peoples R China

来源：

NEUROCOMPUTING | 2020年 / 384卷

基金：

国家重点研发计划;

关键词：

Finite-time synchronization; Switched neural networks; Aperiodically intermittent control; EXPONENTIAL SYNCHRONIZATION; VARYING DELAYS; STABILIZATION; STABILITY; SYSTEMS; NOISE;

D O I：

10.1016/j.neucom.2019.12.031

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 problem for switched neural networks with state-dependent switching under intermittent control is discussed. Different from previous literature, this paper uses aperiodically intermittent control to make switched neural networks achieve finite-time synchronization. A new differential inequality is established to get our main results. Meanwhile, based on graph theory and differential inclusions theory, a proper Lyapunov function is proposed to derive a criterion to ensure finite-time synchronization of switched neural networks. And the convergence time, closely related to the topological structure of networks, is obtained and does not rely on control widths or rest widths for aperiodically intermittent control. Finally, a numerical example is presented to illustrate the effectiveness and feasibility of our results. (C) 2019 Elsevier B.V. All rights reserved.

引用

页码：325 / 334

页数：10

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