Fixed-time synchronization of nonlinear coupled memristive neural networks with time delays via sliding-mode control-Reference-Cited by-同舟云学术

Fixed-time synchronization of nonlinear coupled memristive neural networks with time delays via sliding-mode control

Published:2023 Issue:6 Volume:31 Page:3291-3308
ISSN:2688-1594
Container-title:Electronic Research Archive
language:
Short-container-title:era

Author:

Geng Xingting¹,Feng Jianwen¹,Zhao Yi¹,Li Na²,Wang Jingyi¹

Affiliation:

1. College of Mathematics and Statistics, Shenzhen University, Shenzhen 518060, PR China

2. College of Mathematics and Statistics, Henan University, Kaifeng 475004, PR China

Abstract

<abstract><p>This article focuses on achieving fixed-time synchronization (FxTS) of nonlinear coupled memristive neural networks (NCMMN) with time delays. We propose a novel integrable sliding-mode manifold (SMM) and develop two control strategies (chattering or non-chattering) to achieve FxTS. By selecting appropriate parameters, some criteria are established to force the dynamics of NCMMN to reach the designed SMM within a fixed time and remain on it thereafter. Additionally, they provide estimations for the settling time (TST). the validity of our results is demonstrated through several numerical examples.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

General Mathematics

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