Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron model

Autores
Silva, Iacyel G.; Rosso, Osvaldo Aníbal; Vermelho, Marcos V. D.; Lyra, Marcelo L.
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We numerically investigate the ghost stochastic resonance phenomenon induced by a power-law distributed noise in the neuron FitzHugh–Nagumo model. The input noise considered is produced by a Langevin process including both multiplicative and additive Gaussian noise sources. In this process, the power-law decay exponent of the resulting noise distribution is governed by the off-set of the multiplicative noise, thus allowing us to probe both regimes of Gaussian and strongly non-Gaussian noises. Ghost stochastic resonance, i.e., stochastic resonance in a missing fundamental harmonic, occurs in this model. Deviations from the Gaussianity of the input noise are shown to reduce both the additive noise intensity corresponding to the optimal identification of the missing fundamental as well as the number of firing events at the ghost stochastic resonance condition.
Fil: Silva, Iacyel G.. Universidade Federal de Alagoas; Brasil
Fil: Rosso, Osvaldo Aníbal. Universidade Federal de Alagoas; Brasil. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Vermelho, Marcos V. D.. Universidade Federal de Alagoas; Brasil
Fil: Lyra, Marcelo L.. Universidade Federal de Alagoas; Brasil
Materia
Stochastic Resonance
Ghost Resonance
Power-Law Noise
Neuron Model
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/41561
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron modelSilva, Iacyel G.Rosso, Osvaldo AníbalVermelho, Marcos V. D.Lyra, Marcelo L.Stochastic ResonanceGhost ResonancePower-Law NoiseNeuron Modelhttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1We numerically investigate the ghost stochastic resonance phenomenon induced by a power-law distributed noise in the neuron FitzHugh–Nagumo model. The input noise considered is produced by a Langevin process including both multiplicative and additive Gaussian noise sources. In this process, the power-law decay exponent of the resulting noise distribution is governed by the off-set of the multiplicative noise, thus allowing us to probe both regimes of Gaussian and strongly non-Gaussian noises. Ghost stochastic resonance, i.e., stochastic resonance in a missing fundamental harmonic, occurs in this model. Deviations from the Gaussianity of the input noise are shown to reduce both the additive noise intensity corresponding to the optimal identification of the missing fundamental as well as the number of firing events at the ghost stochastic resonance condition.Fil: Silva, Iacyel G.. Universidade Federal de Alagoas; BrasilFil: Rosso, Osvaldo Aníbal. Universidade Federal de Alagoas; Brasil. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Vermelho, Marcos V. D.. Universidade Federal de Alagoas; BrasilFil: Lyra, Marcelo L.. Universidade Federal de Alagoas; BrasilElsevier Science2015-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/41561Silva, Iacyel G.; Rosso, Osvaldo Aníbal; Vermelho, Marcos V. D.; Lyra, Marcelo L.; Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron model; Elsevier Science; Communications In Nonlinear Science And Numerical Simulation; 22; 5-2015; 641-6491007-5704CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.cnsns.2014.06.050info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S100757041400313Xinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:48:37Zoai:ri.conicet.gov.ar:11336/41561instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:48:37.837CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron model
title Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron model
spellingShingle Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron model
Silva, Iacyel G.
Stochastic Resonance
Ghost Resonance
Power-Law Noise
Neuron Model
title_short Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron model
title_full Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron model
title_fullStr Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron model
title_full_unstemmed Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron model
title_sort Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron model
dc.creator.none.fl_str_mv Silva, Iacyel G.
Rosso, Osvaldo Aníbal
Vermelho, Marcos V. D.
Lyra, Marcelo L.
author Silva, Iacyel G.
author_facet Silva, Iacyel G.
Rosso, Osvaldo Aníbal
Vermelho, Marcos V. D.
Lyra, Marcelo L.
author_role author
author2 Rosso, Osvaldo Aníbal
Vermelho, Marcos V. D.
Lyra, Marcelo L.
author2_role author
author
author
dc.subject.none.fl_str_mv Stochastic Resonance
Ghost Resonance
Power-Law Noise
Neuron Model
topic Stochastic Resonance
Ghost Resonance
Power-Law Noise
Neuron Model
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We numerically investigate the ghost stochastic resonance phenomenon induced by a power-law distributed noise in the neuron FitzHugh–Nagumo model. The input noise considered is produced by a Langevin process including both multiplicative and additive Gaussian noise sources. In this process, the power-law decay exponent of the resulting noise distribution is governed by the off-set of the multiplicative noise, thus allowing us to probe both regimes of Gaussian and strongly non-Gaussian noises. Ghost stochastic resonance, i.e., stochastic resonance in a missing fundamental harmonic, occurs in this model. Deviations from the Gaussianity of the input noise are shown to reduce both the additive noise intensity corresponding to the optimal identification of the missing fundamental as well as the number of firing events at the ghost stochastic resonance condition.
Fil: Silva, Iacyel G.. Universidade Federal de Alagoas; Brasil
Fil: Rosso, Osvaldo Aníbal. Universidade Federal de Alagoas; Brasil. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Vermelho, Marcos V. D.. Universidade Federal de Alagoas; Brasil
Fil: Lyra, Marcelo L.. Universidade Federal de Alagoas; Brasil
description We numerically investigate the ghost stochastic resonance phenomenon induced by a power-law distributed noise in the neuron FitzHugh–Nagumo model. The input noise considered is produced by a Langevin process including both multiplicative and additive Gaussian noise sources. In this process, the power-law decay exponent of the resulting noise distribution is governed by the off-set of the multiplicative noise, thus allowing us to probe both regimes of Gaussian and strongly non-Gaussian noises. Ghost stochastic resonance, i.e., stochastic resonance in a missing fundamental harmonic, occurs in this model. Deviations from the Gaussianity of the input noise are shown to reduce both the additive noise intensity corresponding to the optimal identification of the missing fundamental as well as the number of firing events at the ghost stochastic resonance condition.
publishDate 2015
dc.date.none.fl_str_mv 2015-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/41561
Silva, Iacyel G.; Rosso, Osvaldo Aníbal; Vermelho, Marcos V. D.; Lyra, Marcelo L.; Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron model; Elsevier Science; Communications In Nonlinear Science And Numerical Simulation; 22; 5-2015; 641-649
1007-5704
CONICET Digital
CONICET
url http://hdl.handle.net/11336/41561
identifier_str_mv Silva, Iacyel G.; Rosso, Osvaldo Aníbal; Vermelho, Marcos V. D.; Lyra, Marcelo L.; Ghost stochastic resonance induced by a power-law distributed noise in the FitzHugh?Nagumo neuron model; Elsevier Science; Communications In Nonlinear Science And Numerical Simulation; 22; 5-2015; 641-649
1007-5704
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cnsns.2014.06.050
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S100757041400313X
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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