Asymptotic Synchronization of Memristive Cohen-Grossberg Neural Networks with Time-Varying Delays via Event-Triggered Control Scheme

This paper investigates the asymptotic synchronization of memristive Cohen-Grossberg neural networks (MCGNNs) with time-varying delays under event-triggered control (ETC). First, based on the designed feedback controller, some ETC conditions are provided. It is demonstrated that ETC can significantl...

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Detalles Bibliográficos
Autores principales: Yao, Wei, Yu, Fei, Zhang, Jin, Zhou, Ling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9147740/
https://www.ncbi.nlm.nih.gov/pubmed/35630193
http://dx.doi.org/10.3390/mi13050726
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author Yao, Wei
Yu, Fei
Zhang, Jin
Zhou, Ling
author_facet Yao, Wei
Yu, Fei
Zhang, Jin
Zhou, Ling
author_sort Yao, Wei
collection PubMed
description This paper investigates the asymptotic synchronization of memristive Cohen-Grossberg neural networks (MCGNNs) with time-varying delays under event-triggered control (ETC). First, based on the designed feedback controller, some ETC conditions are provided. It is demonstrated that ETC can significantly reduce the update times of the controller and decrease the computing cost. Next, some sufficient conditions are derived to ensure the asymptotic synchronization of MCGNNs with time-varying delays under the ETC method. Finally, a numerical example is provided to verify the correctness and effectiveness of the obtained results.
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spelling pubmed-91477402022-05-29 Asymptotic Synchronization of Memristive Cohen-Grossberg Neural Networks with Time-Varying Delays via Event-Triggered Control Scheme Yao, Wei Yu, Fei Zhang, Jin Zhou, Ling Micromachines (Basel) Article This paper investigates the asymptotic synchronization of memristive Cohen-Grossberg neural networks (MCGNNs) with time-varying delays under event-triggered control (ETC). First, based on the designed feedback controller, some ETC conditions are provided. It is demonstrated that ETC can significantly reduce the update times of the controller and decrease the computing cost. Next, some sufficient conditions are derived to ensure the asymptotic synchronization of MCGNNs with time-varying delays under the ETC method. Finally, a numerical example is provided to verify the correctness and effectiveness of the obtained results. MDPI 2022-04-30 /pmc/articles/PMC9147740/ /pubmed/35630193 http://dx.doi.org/10.3390/mi13050726 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yao, Wei
Yu, Fei
Zhang, Jin
Zhou, Ling
Asymptotic Synchronization of Memristive Cohen-Grossberg Neural Networks with Time-Varying Delays via Event-Triggered Control Scheme
title Asymptotic Synchronization of Memristive Cohen-Grossberg Neural Networks with Time-Varying Delays via Event-Triggered Control Scheme
title_full Asymptotic Synchronization of Memristive Cohen-Grossberg Neural Networks with Time-Varying Delays via Event-Triggered Control Scheme
title_fullStr Asymptotic Synchronization of Memristive Cohen-Grossberg Neural Networks with Time-Varying Delays via Event-Triggered Control Scheme
title_full_unstemmed Asymptotic Synchronization of Memristive Cohen-Grossberg Neural Networks with Time-Varying Delays via Event-Triggered Control Scheme
title_short Asymptotic Synchronization of Memristive Cohen-Grossberg Neural Networks with Time-Varying Delays via Event-Triggered Control Scheme
title_sort asymptotic synchronization of memristive cohen-grossberg neural networks with time-varying delays via event-triggered control scheme
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9147740/
https://www.ncbi.nlm.nih.gov/pubmed/35630193
http://dx.doi.org/10.3390/mi13050726
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