Spiking neural network Based on cusp catastrophe Theory

Detalhes bibliográficos
Autor(a) principal: Huderek, Damian
Data de Publicação: 2019
Outros Autores: Szczȩsny, Szymon, Rato, Raul
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/103321
Resumo: This paper addresses the problem of effective processing using third generation neural networks. The article features two new models of spiking neurons based on the cusp catastrophe theory. The effectiveness of the models is demonstrated with an example of a network composed of three neurons solving the problem of linear inseparability of the XOR function. The proposed solutions are dedicated to hardware implementation using the Edge computing strategy. The paper presents simulation results and outlines further research direction in the field of practical applications and implementations using nanometer cMOS technologies and the current processing mode.
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spelling Spiking neural network Based on cusp catastrophe Theorycusp catastrophedecision support systemspiking neuronXOR problemTheoretical Computer ScienceComputer Science(all)This paper addresses the problem of effective processing using third generation neural networks. The article features two new models of spiking neurons based on the cusp catastrophe theory. The effectiveness of the models is demonstrated with an example of a network composed of three neurons solving the problem of linear inseparability of the XOR function. The proposed solutions are dedicated to hardware implementation using the Edge computing strategy. The paper presents simulation results and outlines further research direction in the field of practical applications and implementations using nanometer cMOS technologies and the current processing mode.DEE - Departamento de Engenharia Electrotécnica e de ComputadoresCTS - Centro de Tecnologia e SistemasUNINOVA-Instituto de Desenvolvimento de Novas TecnologiasRUNHuderek, DamianSzczȩsny, SzymonRato, Raul2020-09-03T23:12:04Z2019-09-012019-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article12application/pdfhttp://hdl.handle.net/10362/103321eng0867-6356PURE: 18929532https://doi.org/10.2478/fcds-2019-0014info: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:RCAAP2024-03-11T04:48:45Zoai:run.unl.pt:10362/103321Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:39:50.911316Repositório 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 Spiking neural network Based on cusp catastrophe Theory
title Spiking neural network Based on cusp catastrophe Theory
spellingShingle Spiking neural network Based on cusp catastrophe Theory
Huderek, Damian
cusp catastrophe
decision support system
spiking neuron
XOR problem
Theoretical Computer Science
Computer Science(all)
title_short Spiking neural network Based on cusp catastrophe Theory
title_full Spiking neural network Based on cusp catastrophe Theory
title_fullStr Spiking neural network Based on cusp catastrophe Theory
title_full_unstemmed Spiking neural network Based on cusp catastrophe Theory
title_sort Spiking neural network Based on cusp catastrophe Theory
author Huderek, Damian
author_facet Huderek, Damian
Szczȩsny, Szymon
Rato, Raul
author_role author
author2 Szczȩsny, Szymon
Rato, Raul
author2_role author
author
dc.contributor.none.fl_str_mv DEE - Departamento de Engenharia Electrotécnica e de Computadores
CTS - Centro de Tecnologia e Sistemas
UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias
RUN
dc.contributor.author.fl_str_mv Huderek, Damian
Szczȩsny, Szymon
Rato, Raul
dc.subject.por.fl_str_mv cusp catastrophe
decision support system
spiking neuron
XOR problem
Theoretical Computer Science
Computer Science(all)
topic cusp catastrophe
decision support system
spiking neuron
XOR problem
Theoretical Computer Science
Computer Science(all)
description This paper addresses the problem of effective processing using third generation neural networks. The article features two new models of spiking neurons based on the cusp catastrophe theory. The effectiveness of the models is demonstrated with an example of a network composed of three neurons solving the problem of linear inseparability of the XOR function. The proposed solutions are dedicated to hardware implementation using the Edge computing strategy. The paper presents simulation results and outlines further research direction in the field of practical applications and implementations using nanometer cMOS technologies and the current processing mode.
publishDate 2019
dc.date.none.fl_str_mv 2019-09-01
2019-09-01T00:00:00Z
2020-09-03T23:12:04Z
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 http://hdl.handle.net/10362/103321
url http://hdl.handle.net/10362/103321
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0867-6356
PURE: 18929532
https://doi.org/10.2478/fcds-2019-0014
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 12
application/pdf
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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