Permutation entropy and its main biomedical and econophysics applications: a review
- Autores
- Zanin, Massimiliano; Zunino, Luciano José; Rosso, Osvaldo A.; Papo, David
- Año de publicación
- 2012
- Idioma
- inglés
- Tipo de recurso
- reseña artículo
- Estado
- versión publicada
- Descripción
- Entropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it. Nevertheless, important information may be codified also in the temporal dynamics, an aspect which is not usually taken into account. The idea of calculating entropy based on permutation patterns (that is, permutations defined by the order relations among values of a time series) has received a lot of attention in the last years, especially for the understanding of complex and chaotic systems. Permutation entropy directly accounts for the temporal information contained in the time series; furthermore, it has the quality of simplicity, robustness and very low computational cost. To celebrate the tenth anniversary of the original work, here we analyze the theoretical foundations of the permutation entropy, as well as the main recent applications to the analysis of economical markets and to the understanding of biomedical systems.
Facultad de Ingeniería - Materia
-
Ciencias Exactas
Ingeniería
econophysics
EEG
epilepsy
forbidden patterns
permutation entropy
Shannon entropy - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/3.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/37664
Ver los metadatos del registro completo
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Permutation entropy and its main biomedical and econophysics applications: a reviewZanin, MassimilianoZunino, Luciano JoséRosso, Osvaldo A.Papo, DavidCiencias ExactasIngenieríaeconophysicsEEGepilepsyforbidden patternspermutation entropyShannon entropyEntropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it. Nevertheless, important information may be codified also in the temporal dynamics, an aspect which is not usually taken into account. The idea of calculating entropy based on permutation patterns (that is, permutations defined by the order relations among values of a time series) has received a lot of attention in the last years, especially for the understanding of complex and chaotic systems. Permutation entropy directly accounts for the temporal information contained in the time series; furthermore, it has the quality of simplicity, robustness and very low computational cost. To celebrate the tenth anniversary of the original work, here we analyze the theoretical foundations of the permutation entropy, as well as the main recent applications to the analysis of economical markets and to the understanding of biomedical systems.Facultad de Ingeniería2012-08info:eu-repo/semantics/reviewinfo:eu-repo/semantics/publishedVersionRevisionhttp://purl.org/coar/resource_type/c_dcae04bcinfo:ar-repo/semantics/resenaArticuloapplication/pdf1553-1577http://sedici.unlp.edu.ar/handle/10915/37664enginfo:eu-repo/semantics/altIdentifier/url/http://www.mdpi.com/1099-4300/14/8/1553info:eu-repo/semantics/altIdentifier/issn/1099-4300info:eu-repo/semantics/altIdentifier/doi/10.3390/e14081553info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/Creative Commons Attribution 3.0 Unported (CC BY 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:29:50Zoai:sedici.unlp.edu.ar:10915/37664Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:29:50.817SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Permutation entropy and its main biomedical and econophysics applications: a review |
title |
Permutation entropy and its main biomedical and econophysics applications: a review |
spellingShingle |
Permutation entropy and its main biomedical and econophysics applications: a review Zanin, Massimiliano Ciencias Exactas Ingeniería econophysics EEG epilepsy forbidden patterns permutation entropy Shannon entropy |
title_short |
Permutation entropy and its main biomedical and econophysics applications: a review |
title_full |
Permutation entropy and its main biomedical and econophysics applications: a review |
title_fullStr |
Permutation entropy and its main biomedical and econophysics applications: a review |
title_full_unstemmed |
Permutation entropy and its main biomedical and econophysics applications: a review |
title_sort |
Permutation entropy and its main biomedical and econophysics applications: a review |
dc.creator.none.fl_str_mv |
Zanin, Massimiliano Zunino, Luciano José Rosso, Osvaldo A. Papo, David |
author |
Zanin, Massimiliano |
author_facet |
Zanin, Massimiliano Zunino, Luciano José Rosso, Osvaldo A. Papo, David |
author_role |
author |
author2 |
Zunino, Luciano José Rosso, Osvaldo A. Papo, David |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
Ciencias Exactas Ingeniería econophysics EEG epilepsy forbidden patterns permutation entropy Shannon entropy |
topic |
Ciencias Exactas Ingeniería econophysics EEG epilepsy forbidden patterns permutation entropy Shannon entropy |
dc.description.none.fl_txt_mv |
Entropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it. Nevertheless, important information may be codified also in the temporal dynamics, an aspect which is not usually taken into account. The idea of calculating entropy based on permutation patterns (that is, permutations defined by the order relations among values of a time series) has received a lot of attention in the last years, especially for the understanding of complex and chaotic systems. Permutation entropy directly accounts for the temporal information contained in the time series; furthermore, it has the quality of simplicity, robustness and very low computational cost. To celebrate the tenth anniversary of the original work, here we analyze the theoretical foundations of the permutation entropy, as well as the main recent applications to the analysis of economical markets and to the understanding of biomedical systems. Facultad de Ingeniería |
description |
Entropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it. Nevertheless, important information may be codified also in the temporal dynamics, an aspect which is not usually taken into account. The idea of calculating entropy based on permutation patterns (that is, permutations defined by the order relations among values of a time series) has received a lot of attention in the last years, especially for the understanding of complex and chaotic systems. Permutation entropy directly accounts for the temporal information contained in the time series; furthermore, it has the quality of simplicity, robustness and very low computational cost. To celebrate the tenth anniversary of the original work, here we analyze the theoretical foundations of the permutation entropy, as well as the main recent applications to the analysis of economical markets and to the understanding of biomedical systems. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-08 |
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review |
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publishedVersion |
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http://sedici.unlp.edu.ar/handle/10915/37664 |
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eng |
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eng |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/3.0/ Creative Commons Attribution 3.0 Unported (CC BY 3.0) |
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openAccess |
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