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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/84122
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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 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://sedici.unlp.edu.ar/handle/10915/84122 |
url |
http://sedici.unlp.edu.ar/handle/10915/84122 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
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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 |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf 2421-2428 |
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