Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis

Autores
Zunino, Luciano José; Olivares, Felipe; Ribeiro, Haroldo V.; Rosso, Osvaldo Aníbal
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The main motivation of this paper is to introduce the permutation Jensen-Shannon distance, a symbolic tool able to quantify the degree of similarity between two arbitrary time series. This quantifier results from the fusion of two concepts, the Jensen-Shannon divergence and the encoding scheme based on the sequential ordering of the elements in the data series. The versatility and robustness of this ordinal symbolic distance for characterizing and discriminating different dynamics are illustrated through several numerical and experimental applications. Results obtained allow us to be optimistic about its usefulness in the field of complex time-series analysis. Moreover, thanks to its simplicity, low computational cost, wide applicability, and less susceptibility to outliers and artifacts, this ordinal measure can efficiently handle large amounts of data and help to tackle the current big data challenges.
Fil: Zunino, Luciano José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Ópticas. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones Ópticas. Universidad Nacional de La Plata. Centro de Investigaciones Ópticas; Argentina
Fil: Olivares, Felipe. No especifíca;
Fil: Ribeiro, Haroldo V.. UNIVERSIDADE ESTADUAL DE MARINGÁ (UEM);
Fil: Rosso, Osvaldo Aníbal. Universidade Federal de Alagoas; Brasil. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
complexity
non linear dynamics
computational cost
Jensen-Shannon
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:11336/211618
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysisZunino, Luciano JoséOlivares, FelipeRibeiro, Haroldo V.Rosso, Osvaldo Aníbalcomplexitynon linear dynamicscomputational costJensen-Shannonhttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1The main motivation of this paper is to introduce the permutation Jensen-Shannon distance, a symbolic tool able to quantify the degree of similarity between two arbitrary time series. This quantifier results from the fusion of two concepts, the Jensen-Shannon divergence and the encoding scheme based on the sequential ordering of the elements in the data series. The versatility and robustness of this ordinal symbolic distance for characterizing and discriminating different dynamics are illustrated through several numerical and experimental applications. Results obtained allow us to be optimistic about its usefulness in the field of complex time-series analysis. Moreover, thanks to its simplicity, low computational cost, wide applicability, and less susceptibility to outliers and artifacts, this ordinal measure can efficiently handle large amounts of data and help to tackle the current big data challenges.Fil: Zunino, Luciano José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Ópticas. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones Ópticas. Universidad Nacional de La Plata. Centro de Investigaciones Ópticas; ArgentinaFil: Olivares, Felipe. No especifíca;Fil: Ribeiro, Haroldo V.. UNIVERSIDADE ESTADUAL DE MARINGÁ (UEM);Fil: Rosso, Osvaldo Aníbal. Universidade Federal de Alagoas; Brasil. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaAmerican Physical Society2022-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/211618Zunino, Luciano José; Olivares, Felipe; Ribeiro, Haroldo V.; Rosso, Osvaldo Aníbal; Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis; American Physical Society; Physical Review E; 105; 4; 4-2022; 1-212470-00452470-0053CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1103/PhysRevE.105.045310info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-05-13T11:11:28Zoai:ri.conicet.gov.ar:11336/211618instacron: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:34982026-05-13 11:11:28.751CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis
title Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis
spellingShingle Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis
Zunino, Luciano José
complexity
non linear dynamics
computational cost
Jensen-Shannon
title_short Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis
title_full Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis
title_fullStr Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis
title_full_unstemmed Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis
title_sort Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis
dc.creator.none.fl_str_mv Zunino, Luciano José
Olivares, Felipe
Ribeiro, Haroldo V.
Rosso, Osvaldo Aníbal
author Zunino, Luciano José
author_facet Zunino, Luciano José
Olivares, Felipe
Ribeiro, Haroldo V.
Rosso, Osvaldo Aníbal
author_role author
author2 Olivares, Felipe
Ribeiro, Haroldo V.
Rosso, Osvaldo Aníbal
author2_role author
author
author
dc.subject.none.fl_str_mv complexity
non linear dynamics
computational cost
Jensen-Shannon
topic complexity
non linear dynamics
computational cost
Jensen-Shannon
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The main motivation of this paper is to introduce the permutation Jensen-Shannon distance, a symbolic tool able to quantify the degree of similarity between two arbitrary time series. This quantifier results from the fusion of two concepts, the Jensen-Shannon divergence and the encoding scheme based on the sequential ordering of the elements in the data series. The versatility and robustness of this ordinal symbolic distance for characterizing and discriminating different dynamics are illustrated through several numerical and experimental applications. Results obtained allow us to be optimistic about its usefulness in the field of complex time-series analysis. Moreover, thanks to its simplicity, low computational cost, wide applicability, and less susceptibility to outliers and artifacts, this ordinal measure can efficiently handle large amounts of data and help to tackle the current big data challenges.
Fil: Zunino, Luciano José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Ópticas. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones Ópticas. Universidad Nacional de La Plata. Centro de Investigaciones Ópticas; Argentina
Fil: Olivares, Felipe. No especifíca;
Fil: Ribeiro, Haroldo V.. UNIVERSIDADE ESTADUAL DE MARINGÁ (UEM);
Fil: Rosso, Osvaldo Aníbal. Universidade Federal de Alagoas; Brasil. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description The main motivation of this paper is to introduce the permutation Jensen-Shannon distance, a symbolic tool able to quantify the degree of similarity between two arbitrary time series. This quantifier results from the fusion of two concepts, the Jensen-Shannon divergence and the encoding scheme based on the sequential ordering of the elements in the data series. The versatility and robustness of this ordinal symbolic distance for characterizing and discriminating different dynamics are illustrated through several numerical and experimental applications. Results obtained allow us to be optimistic about its usefulness in the field of complex time-series analysis. Moreover, thanks to its simplicity, low computational cost, wide applicability, and less susceptibility to outliers and artifacts, this ordinal measure can efficiently handle large amounts of data and help to tackle the current big data challenges.
publishDate 2022
dc.date.none.fl_str_mv 2022-04
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/11336/211618
Zunino, Luciano José; Olivares, Felipe; Ribeiro, Haroldo V.; Rosso, Osvaldo Aníbal; Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis; American Physical Society; Physical Review E; 105; 4; 4-2022; 1-21
2470-0045
2470-0053
CONICET Digital
CONICET
url http://hdl.handle.net/11336/211618
identifier_str_mv Zunino, Luciano José; Olivares, Felipe; Ribeiro, Haroldo V.; Rosso, Osvaldo Aníbal; Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis; American Physical Society; Physical Review E; 105; 4; 4-2022; 1-21
2470-0045
2470-0053
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1103/PhysRevE.105.045310
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
application/pdf
dc.publisher.none.fl_str_mv American Physical Society
publisher.none.fl_str_mv American Physical Society
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
_version_ 1865200369619959808
score 13.115601

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