An alternative computation of the entropy of 1D signals based on geometric properties

Autores
Bonini, Cristian; Rey, Andrea; Otero, Dino; Amadio, Ariel; García Blesa, Manuel; Legnani, Walter
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The objective of this work is to present a novel methodology based on the computation of a couple of geometric characteristics of the position of the data points in 1D signal to propose an alternative estimation of signal entropy. The conditions to be fulfilled by the signal are minimal; only those necessary to meet the sampling theorem requirement are enough. This work shows some examples in which the proposed methodology can distinguish among signals that cannot be differentiated by other in-use alternatives. Additionally an original example where the usual ordinal pattern algorithm to compute entropy is not applicable, is presented and analyzed. The proposal developed through this work carries some advantages over other alternatives and constitutes a true advancement in the pathway to compute the distribution function of the sequential points of 1D signals later used to compute the entropy of the signal.
UTN FRBA
Fil: Bonini, Cristian. Universidad Tecnológica Nacional. Facultad Regional General Pacheco. Center of Research, Development and Innovation in Electric Energy; Argentina.
Fil: Rey, Andrea. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Center of Signal and Image Processing; Argentina
Fil: Otero, Dino. Universidad Tecnológica Nacional. Facultad Regional General Pacheco. Center of Vehicle Research, Development and Innovation; Argentina.
Fil: Amadio, Ariel. Universidad Tecnológica Nacional. Facultad Regional General Pacheco. Center of Vehicle Research, Development and Innovation; Argentina.
Fil: García Blesa, Manuel. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Center of Signal and Image Processing; Argentina
Fil: Legnani, Walter. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Center of Signal and Image Processing; Argentina
Peer Reviewed
Fuente
Stat., Optim. Inf. Comput. 10, 998–1020. (2022)
Materia
Order Pattern Distribution
Permutation Entropy
Symbolic Dynamics
Signal Entropy
Data Points Geometry
Nivel de accesibilidad
acceso abierto
Condiciones de uso
2024-03-19T20:26:33Z
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/9921
Acceder
id RIAUTN_66e96b92412dfd4fea73548f86ee54df
oai_identifier_str oai:ria.utn.edu.ar:20.500.12272/9921
network_acronym_str RIAUTN
repository_id_str a
network_name_str Repositorio Institucional Abierto (UTN)
spelling An alternative computation of the entropy of 1D signals based on geometric propertiesBonini, CristianRey, AndreaOtero, DinoAmadio, ArielGarcía Blesa, ManuelLegnani, WalterOrder Pattern DistributionPermutation EntropySymbolic DynamicsSignal EntropyData Points GeometryThe objective of this work is to present a novel methodology based on the computation of a couple of geometric characteristics of the position of the data points in 1D signal to propose an alternative estimation of signal entropy. The conditions to be fulfilled by the signal are minimal; only those necessary to meet the sampling theorem requirement are enough. This work shows some examples in which the proposed methodology can distinguish among signals that cannot be differentiated by other in-use alternatives. Additionally an original example where the usual ordinal pattern algorithm to compute entropy is not applicable, is presented and analyzed. The proposal developed through this work carries some advantages over other alternatives and constitutes a true advancement in the pathway to compute the distribution function of the sequential points of 1D signals later used to compute the entropy of the signal.UTN FRBAFil: Bonini, Cristian. Universidad Tecnológica Nacional. Facultad Regional General Pacheco. Center of Research, Development and Innovation in Electric Energy; Argentina.Fil: Rey, Andrea. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Center of Signal and Image Processing; ArgentinaFil: Otero, Dino. Universidad Tecnológica Nacional. Facultad Regional General Pacheco. Center of Vehicle Research, Development and Innovation; Argentina.Fil: Amadio, Ariel. Universidad Tecnológica Nacional. Facultad Regional General Pacheco. Center of Vehicle Research, Development and Innovation; Argentina.Fil: García Blesa, Manuel. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Center of Signal and Image Processing; ArgentinaFil: Legnani, Walter. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Center of Signal and Image Processing; ArgentinaPeer Reviewed2024-03-19T20:26:33Z2024-03-19T20:26:33Z2022-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articulopdfapplication/pdfStat., Optim. Inf. Comput., Vol. 10http://hdl.handle.net/20.500.12272/992110.19139/soic-2310-5070-1523Stat., Optim. Inf. Comput. 10, 998–1020. (2022)reponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica NacionalengASTCABA0008120info:eu-repo/semantics/openAccess2024-03-19T20:26:33Zhttp://creativecommons.org/licenses/by-nc-sa/4.0/Atribución-NoComercial-CompartirIgual 4.0 InternacionalCristian Bonini , Andrea Rey, Dino Otero, Ariel Amadio, Manuel García Blesa, Walter LegnaniLicencia Creative Commons Atribución- No Comercial2026-09-24T12:44:48Zoai:ria.utn.edu.ar:20.500.12272/9921instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-09-24 12:44:48.786Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv An alternative computation of the entropy of 1D signals based on geometric properties
title An alternative computation of the entropy of 1D signals based on geometric properties
spellingShingle An alternative computation of the entropy of 1D signals based on geometric properties
Bonini, Cristian
Order Pattern Distribution
Permutation Entropy
Symbolic Dynamics
Signal Entropy
Data Points Geometry
title_short An alternative computation of the entropy of 1D signals based on geometric properties
title_full An alternative computation of the entropy of 1D signals based on geometric properties
title_fullStr An alternative computation of the entropy of 1D signals based on geometric properties
title_full_unstemmed An alternative computation of the entropy of 1D signals based on geometric properties
title_sort An alternative computation of the entropy of 1D signals based on geometric properties
dc.creator.none.fl_str_mv Bonini, Cristian
Rey, Andrea
Otero, Dino
Amadio, Ariel
García Blesa, Manuel
Legnani, Walter
author Bonini, Cristian
author_facet Bonini, Cristian
Rey, Andrea
Otero, Dino
Amadio, Ariel
García Blesa, Manuel
Legnani, Walter
author_role author
author2 Rey, Andrea
Otero, Dino
Amadio, Ariel
García Blesa, Manuel
Legnani, Walter
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Order Pattern Distribution
Permutation Entropy
Symbolic Dynamics
Signal Entropy
Data Points Geometry
topic Order Pattern Distribution
Permutation Entropy
Symbolic Dynamics
Signal Entropy
Data Points Geometry
dc.description.none.fl_txt_mv The objective of this work is to present a novel methodology based on the computation of a couple of geometric characteristics of the position of the data points in 1D signal to propose an alternative estimation of signal entropy. The conditions to be fulfilled by the signal are minimal; only those necessary to meet the sampling theorem requirement are enough. This work shows some examples in which the proposed methodology can distinguish among signals that cannot be differentiated by other in-use alternatives. Additionally an original example where the usual ordinal pattern algorithm to compute entropy is not applicable, is presented and analyzed. The proposal developed through this work carries some advantages over other alternatives and constitutes a true advancement in the pathway to compute the distribution function of the sequential points of 1D signals later used to compute the entropy of the signal.
UTN FRBA
Fil: Bonini, Cristian. Universidad Tecnológica Nacional. Facultad Regional General Pacheco. Center of Research, Development and Innovation in Electric Energy; Argentina.
Fil: Rey, Andrea. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Center of Signal and Image Processing; Argentina
Fil: Otero, Dino. Universidad Tecnológica Nacional. Facultad Regional General Pacheco. Center of Vehicle Research, Development and Innovation; Argentina.
Fil: Amadio, Ariel. Universidad Tecnológica Nacional. Facultad Regional General Pacheco. Center of Vehicle Research, Development and Innovation; Argentina.
Fil: García Blesa, Manuel. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Center of Signal and Image Processing; Argentina
Fil: Legnani, Walter. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Center of Signal and Image Processing; Argentina
Peer Reviewed
description The objective of this work is to present a novel methodology based on the computation of a couple of geometric characteristics of the position of the data points in 1D signal to propose an alternative estimation of signal entropy. The conditions to be fulfilled by the signal are minimal; only those necessary to meet the sampling theorem requirement are enough. This work shows some examples in which the proposed methodology can distinguish among signals that cannot be differentiated by other in-use alternatives. Additionally an original example where the usual ordinal pattern algorithm to compute entropy is not applicable, is presented and analyzed. The proposal developed through this work carries some advantages over other alternatives and constitutes a true advancement in the pathway to compute the distribution function of the sequential points of 1D signals later used to compute the entropy of the signal.
publishDate 2022
dc.date.none.fl_str_mv 2022-09-01
2024-03-19T20:26:33Z
2024-03-19T20:26:33Z
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 Stat., Optim. Inf. Comput., Vol. 10
http://hdl.handle.net/20.500.12272/9921
10.19139/soic-2310-5070-1523
identifier_str_mv Stat., Optim. Inf. Comput., Vol. 10
10.19139/soic-2310-5070-1523
url http://hdl.handle.net/20.500.12272/9921
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv ASTCABA0008120
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
2024-03-19T20:26:33Z
http://creativecommons.org/licenses/by-nc-sa/4.0/
Atribución-NoComercial-CompartirIgual 4.0 Internacional
Cristian Bonini , Andrea Rey, Dino Otero, Ariel Amadio, Manuel García Blesa, Walter Legnani
Licencia Creative Commons Atribución- No Comercial
eu_rights_str_mv openAccess
rights_invalid_str_mv 2024-03-19T20:26:33Z
http://creativecommons.org/licenses/by-nc-sa/4.0/
Atribución-NoComercial-CompartirIgual 4.0 Internacional
Cristian Bonini , Andrea Rey, Dino Otero, Ariel Amadio, Manuel García Blesa, Walter Legnani
Licencia Creative Commons Atribución- No Comercial
dc.format.none.fl_str_mv pdf
application/pdf
dc.source.none.fl_str_mv Stat., Optim. Inf. Comput. 10, 998–1020. (2022)
reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
_version_ 1877230887648624640
score 13.265058

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