Complexity-entropy causality plane: a useful approach for distinguishing songs

Autores
Ribeiro, Haroldo V.; Zunino, Luciano José; Mendes, Renio S.; Lenzi, Ervin K.
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Nowadays we are often faced with huge databases resulting from the rapid growth of data storage technologies. This is particularly true when dealing with music databases. In this context, it is essential to have techniques and tools able to discriminate properties from these massive sets. In this work, we report on a statistical analysis of more than ten thousand songs aiming to obtain a complexity hierarchy. Our approach is based on the estimation of the permutation entropy combined with an intensive complexity measure, building up the Complexity-entropy causality plane. The results obtained indicate that this representation space is very promising to discriminate songs as well as to allow a relative quantitative comparison among songs. Additionally, we believe that the here-reported method may be applied in practical situations since it is simple, robust and has a fast numerical implementation.
Facultad de Ingeniería
Materia
Ingeniería
Física
Complexity measure
Music
Permutation entropy
Time series analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/84122

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network_name_str SEDICI (UNLP)
spelling Complexity-entropy causality plane: a useful approach for distinguishing songsRibeiro, Haroldo V.Zunino, Luciano JoséMendes, Renio S.Lenzi, Ervin K.IngenieríaFísicaComplexity measureMusicPermutation entropyTime series analysisNowadays we are often faced with huge databases resulting from the rapid growth of data storage technologies. This is particularly true when dealing with music databases. In this context, it is essential to have techniques and tools able to discriminate properties from these massive sets. In this work, we report on a statistical analysis of more than ten thousand songs aiming to obtain a complexity hierarchy. Our approach is based on the estimation of the permutation entropy combined with an intensive complexity measure, building up the Complexity-entropy causality plane. The results obtained indicate that this representation space is very promising to discriminate songs as well as to allow a relative quantitative comparison among songs. Additionally, we believe that the here-reported method may be applied in practical situations since it is simple, robust and has a fast numerical implementation.Facultad de Ingeniería2012info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf2421-2428http://sedici.unlp.edu.ar/handle/10915/84122enginfo:eu-repo/semantics/altIdentifier/issn/0378-4371info:eu-repo/semantics/altIdentifier/doi/10.1016/j.physa.2011.12.009info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-17T09:58:49Zoai:sedici.unlp.edu.ar:10915/84122Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-17 09:58:49.331SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Complexity-entropy causality plane: a useful approach for distinguishing songs
title Complexity-entropy causality plane: a useful approach for distinguishing songs
spellingShingle Complexity-entropy causality plane: a useful approach for distinguishing songs
Ribeiro, Haroldo V.
Ingeniería
Física
Complexity measure
Music
Permutation entropy
Time series analysis
title_short Complexity-entropy causality plane: a useful approach for distinguishing songs
title_full Complexity-entropy causality plane: a useful approach for distinguishing songs
title_fullStr Complexity-entropy causality plane: a useful approach for distinguishing songs
title_full_unstemmed Complexity-entropy causality plane: a useful approach for distinguishing songs
title_sort Complexity-entropy causality plane: a useful approach for distinguishing songs
dc.creator.none.fl_str_mv Ribeiro, Haroldo V.
Zunino, Luciano José
Mendes, Renio S.
Lenzi, Ervin K.
author Ribeiro, Haroldo V.
author_facet Ribeiro, Haroldo V.
Zunino, Luciano José
Mendes, Renio S.
Lenzi, Ervin K.
author_role author
author2 Zunino, Luciano José
Mendes, Renio S.
Lenzi, Ervin K.
author2_role author
author
author
dc.subject.none.fl_str_mv Ingeniería
Física
Complexity measure
Music
Permutation entropy
Time series analysis
topic Ingeniería
Física
Complexity measure
Music
Permutation entropy
Time series analysis
dc.description.none.fl_txt_mv Nowadays we are often faced with huge databases resulting from the rapid growth of data storage technologies. This is particularly true when dealing with music databases. In this context, it is essential to have techniques and tools able to discriminate properties from these massive sets. In this work, we report on a statistical analysis of more than ten thousand songs aiming to obtain a complexity hierarchy. Our approach is based on the estimation of the permutation entropy combined with an intensive complexity measure, building up the Complexity-entropy causality plane. The results obtained indicate that this representation space is very promising to discriminate songs as well as to allow a relative quantitative comparison among songs. Additionally, we believe that the here-reported method may be applied in practical situations since it is simple, robust and has a fast numerical implementation.
Facultad de Ingeniería
description Nowadays we are often faced with huge databases resulting from the rapid growth of data storage technologies. This is particularly true when dealing with music databases. In this context, it is essential to have techniques and tools able to discriminate properties from these massive sets. In this work, we report on a statistical analysis of more than ten thousand songs aiming to obtain a complexity hierarchy. Our approach is based on the estimation of the permutation entropy combined with an intensive complexity measure, building up the Complexity-entropy causality plane. The results obtained indicate that this representation space is very promising to discriminate songs as well as to allow a relative quantitative comparison among songs. Additionally, we believe that the here-reported method may be applied in practical situations since it is simple, robust and has a fast numerical implementation.
publishDate 2012
dc.date.none.fl_str_mv 2012
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/84122
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/0378-4371
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.physa.2011.12.009
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
2421-2428
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instname:Universidad Nacional de La Plata
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reponame_str SEDICI (UNLP)
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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