Synchronization in Fractional-Order Complex-Valued Delayed Neural Networks

This paper discusses the synchronization of fractional order complex valued neural networks (FOCVNN) at the presence of time delay. Synchronization criterions are achieved through the employment of a linear feedback control and comparison theorem of fractional order linear systems with delay. Feasib...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Weiwei, Cao, Jinde, Chen, Dingyuan, Alsaadi, Fuad E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512252/
https://www.ncbi.nlm.nih.gov/pubmed/33265140
http://dx.doi.org/10.3390/e20010054
_version_ 1783586115140190208
author Zhang, Weiwei
Cao, Jinde
Chen, Dingyuan
Alsaadi, Fuad E.
author_facet Zhang, Weiwei
Cao, Jinde
Chen, Dingyuan
Alsaadi, Fuad E.
author_sort Zhang, Weiwei
collection PubMed
description This paper discusses the synchronization of fractional order complex valued neural networks (FOCVNN) at the presence of time delay. Synchronization criterions are achieved through the employment of a linear feedback control and comparison theorem of fractional order linear systems with delay. Feasibility and effectiveness of the proposed system are validated through numerical simulations.
format Online
Article
Text
id pubmed-7512252
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-75122522020-11-09 Synchronization in Fractional-Order Complex-Valued Delayed Neural Networks Zhang, Weiwei Cao, Jinde Chen, Dingyuan Alsaadi, Fuad E. Entropy (Basel) Article This paper discusses the synchronization of fractional order complex valued neural networks (FOCVNN) at the presence of time delay. Synchronization criterions are achieved through the employment of a linear feedback control and comparison theorem of fractional order linear systems with delay. Feasibility and effectiveness of the proposed system are validated through numerical simulations. MDPI 2018-01-12 /pmc/articles/PMC7512252/ /pubmed/33265140 http://dx.doi.org/10.3390/e20010054 Text en © 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Weiwei
Cao, Jinde
Chen, Dingyuan
Alsaadi, Fuad E.
Synchronization in Fractional-Order Complex-Valued Delayed Neural Networks
title Synchronization in Fractional-Order Complex-Valued Delayed Neural Networks
title_full Synchronization in Fractional-Order Complex-Valued Delayed Neural Networks
title_fullStr Synchronization in Fractional-Order Complex-Valued Delayed Neural Networks
title_full_unstemmed Synchronization in Fractional-Order Complex-Valued Delayed Neural Networks
title_short Synchronization in Fractional-Order Complex-Valued Delayed Neural Networks
title_sort synchronization in fractional-order complex-valued delayed neural networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512252/
https://www.ncbi.nlm.nih.gov/pubmed/33265140
http://dx.doi.org/10.3390/e20010054
work_keys_str_mv AT zhangweiwei synchronizationinfractionalordercomplexvalueddelayedneuralnetworks
AT caojinde synchronizationinfractionalordercomplexvalueddelayedneuralnetworks
AT chendingyuan synchronizationinfractionalordercomplexvalueddelayedneuralnetworks
AT alsaadifuade synchronizationinfractionalordercomplexvalueddelayedneuralnetworks

Ejemplares similares