Global exponential stability of discrete-time Hopfield neural network models with unbounded delays

Detalhes bibliográficos
Autor(a) principal: Oliveira, José J.
Data de Publicação: 2022
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/1822/78376
Resumo: In this paper, a general setting is presented to study the exponential stability of discrete-time systems with bounded or unbounded delays. Based on the M-matrix theory, we establish sufficient conditions to ensure the global exponential stability of the zero equilibrium of low-order, and high-order, discrete-time Hopfield neural network models with unbounded delays and delay in the leakage terms. A comparison of the literature shows that our results generalize and improve some in recent publications.
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spelling Global exponential stability of discrete-time Hopfield neural network models with unbounded delaysNeural networksDelay difference equationsUnbounded delaysGlobal stabilityCiências Naturais::MatemáticasScience & TechnologyIn this paper, a general setting is presented to study the exponential stability of discrete-time systems with bounded or unbounded delays. Based on the M-matrix theory, we establish sufficient conditions to ensure the global exponential stability of the zero equilibrium of low-order, and high-order, discrete-time Hopfield neural network models with unbounded delays and delay in the leakage terms. A comparison of the literature shows that our results generalize and improve some in recent publications.Fundação para a Ciência e Tecnologia (FCT) UIDB/00013/2020 and UIDP/00013/2020Taylor & FrancisUniversidade do MinhoOliveira, José J.2022-05-162022-05-16T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/78376eng1023-61981563-512010.1080/10236198.2022.2073820https://www.tandfonline.com/doi/full/10.1080/10236198.2022.2073820info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T11:54:15Zoai:repositorium.sdum.uminho.pt:1822/78376Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:43:44.725953Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Global exponential stability of discrete-time Hopfield neural network models with unbounded delays
title Global exponential stability of discrete-time Hopfield neural network models with unbounded delays
spellingShingle Global exponential stability of discrete-time Hopfield neural network models with unbounded delays
Oliveira, José J.
Neural networks
Delay difference equations
Unbounded delays
Global stability
Ciências Naturais::Matemáticas
Science & Technology
title_short Global exponential stability of discrete-time Hopfield neural network models with unbounded delays
title_full Global exponential stability of discrete-time Hopfield neural network models with unbounded delays
title_fullStr Global exponential stability of discrete-time Hopfield neural network models with unbounded delays
title_full_unstemmed Global exponential stability of discrete-time Hopfield neural network models with unbounded delays
title_sort Global exponential stability of discrete-time Hopfield neural network models with unbounded delays
author Oliveira, José J.
author_facet Oliveira, José J.
author_role author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Oliveira, José J.
dc.subject.por.fl_str_mv Neural networks
Delay difference equations
Unbounded delays
Global stability
Ciências Naturais::Matemáticas
Science & Technology
topic Neural networks
Delay difference equations
Unbounded delays
Global stability
Ciências Naturais::Matemáticas
Science & Technology
description In this paper, a general setting is presented to study the exponential stability of discrete-time systems with bounded or unbounded delays. Based on the M-matrix theory, we establish sufficient conditions to ensure the global exponential stability of the zero equilibrium of low-order, and high-order, discrete-time Hopfield neural network models with unbounded delays and delay in the leakage terms. A comparison of the literature shows that our results generalize and improve some in recent publications.
publishDate 2022
dc.date.none.fl_str_mv 2022-05-16
2022-05-16T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1822/78376
url https://hdl.handle.net/1822/78376
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1023-6198
1563-5120
10.1080/10236198.2022.2073820
https://www.tandfonline.com/doi/full/10.1080/10236198.2022.2073820
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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