Publicação
Global exponential stability of discrete-time Hopfield neural network models with unbounded delays
| 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. |
|---|---|
| Autores principais: | Oliveira, José J. |
| Assunto: | Neural networks Delay difference equations Unbounded delays Global stability |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| _version_ | 1866875376904437761 |
|---|---|
| author | Oliveira, José J. |
| author_facet | Oliveira, José J. |
| author_role | author |
| contributor_name_str_mv | Universidade do Minho |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Oliveira, José J.\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Universidade do Minho |
| datacite.creators.creator.creatorName.fl_str_mv | Oliveira, José J. |
| datacite.date.Accepted.fl_str_mv | 2022-05-16T00:00:00Z |
| datacite.date.available.fl_str_mv | 2022-11-16T07:00:28Z |
| datacite.date.embargoed.fl_str_mv | 2022-11-16T07:00:28Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Neural networks Delay difference equations Unbounded delays Global stability |
| datacite.titles.title.fl_str_mv | Global exponential stability of discrete-time Hopfield neural network models with unbounded delays |
| dc.contributor.none.fl_str_mv | Universidade do Minho |
| dc.creator.none.fl_str_mv | Oliveira, José J. |
| dc.date.Accepted.fl_str_mv | 2022-05-16T00:00:00Z |
| dc.date.available.fl_str_mv | 2022-11-16T07:00:28Z |
| dc.date.embargoed.fl_str_mv | 2022-11-16T07:00:28Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://hdl.handle.net/1822/78376 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Taylor & Francis |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Neural networks Delay difference equations Unbounded delays Global stability |
| dc.title.fl_str_mv | Global exponential stability of discrete-time Hopfield neural network models with unbounded delays |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| 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. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://prod-dspace.uminho.pt/bitstreams/1ecee61b-6286-4c22-b27d-1a4f0938f775/download |
| id | rum_8ea0d247ebd2d88c085e09ae4be3db96 |
| identifier.url.fl_str_mv | https://hdl.handle.net/1822/78376 |
| instacron_str | repositorium |
| institution | Universidade do Minho |
| instname_str | Universidade do Minho |
| language | eng |
| network_acronym_str | rum |
| network_name_str | RepositóriUM - Universidade do Minho |
| oai_identifier_str | oai:repositorium.uminho.pt:1822/78376 |
| organization_str_mv | urn:organizationAcronym:repositorium |
| person_str_mv | Oliveira, José J. |
| publishDate | 2022 |
| publisher.none.fl_str_mv | Taylor & Francis |
| reponame_str | RepositóriUM - Universidade do Minho |
| repository_id_str | urn:repositoryAcronym:rum |
| service_str_mv | urn:repositoryAcronym:rum |
| spelling | engTaylor & FrancisporIn 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.application/pdfporGlobal exponential stability of discrete-time Hopfield neural network models with unbounded delaysOliveira, José J.HostingInstitutionOrganizationalUniversidade do Minhoe-mailmailto:repositorium@usdb.uminho.ptrepositorium@usdb.uminho.ptISSNIsPartOf1023-6198DOIIsPartOf10.1080/10236198.2022.20738202022-11-16T07:00:28Z2022-05-162022-05-16T00:00:00ZHandlehttps://hdl.handle.net/1822/78376http://purl.org/coar/access_right/c_abf2open accessNeural networksDelay difference equationsUnbounded delaysGlobal stability850680 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://prod-dspace.uminho.pt/bitstreams/1ecee61b-6286-4c22-b27d-1a4f0938f775/download |
| 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 |
| status | SINGLETON |
| subject.fl_str_mv | Neural networks Delay difference equations Unbounded delays Global stability |
| title | 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_short | 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 |
| topic | Neural networks Delay difference equations Unbounded delays Global stability |
| topic_facet | Neural networks Delay difference equations Unbounded delays Global stability |
| url | https://hdl.handle.net/1822/78376 |
| visible | 1 |