Distinguishing noise from chaos
- Autores
- Rosso, Osvaldo A.; Larrondo, Hilda Ángela; Martín, María Teresa; Plastino, Ángel Luis; Fuentes, Miguel A.
- Año de publicación
- 2007
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Chaotic systems share with stochastic processes several properties that make them almost undistinguishable. In this communication we introduce a representation space, to be called the complexity-entropy causality plane. Its horizontal and vertical axis are suitable functionals of the pertinent probability distribution, namely, the entropy of the system and an appropriate statistical complexity measure, respectively. These two functionals are evaluated using the Bandt-Pompe recipe to assign a probability distribution function to the time series generated by the system. Several well-known model-generated time series, usually regarded as being of either stochastic or chaotic nature, are analyzed so as to illustrate the approach. The main achievement of this communication is the possibility of clearly distinguishing between them in our representation space, something that is rather difficult otherwise.
Instituto de Física La Plata - Materia
-
Física
Ciencias Exactas
Chaotic systems
Entropy (information theory)
Representation space - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/126151
Ver los metadatos del registro completo
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Distinguishing noise from chaosRosso, Osvaldo A.Larrondo, Hilda ÁngelaMartín, María TeresaPlastino, Ángel LuisFuentes, Miguel A.FísicaCiencias ExactasChaotic systemsEntropy (information theory)Representation spaceChaotic systems share with stochastic processes several properties that make them almost undistinguishable. In this communication we introduce a representation space, to be called the complexity-entropy causality plane. Its horizontal and vertical axis are suitable functionals of the pertinent probability distribution, namely, the entropy of the system and an appropriate statistical complexity measure, respectively. These two functionals are evaluated using the Bandt-Pompe recipe to assign a probability distribution function to the time series generated by the system. Several well-known model-generated time series, usually regarded as being of either stochastic or chaotic nature, are analyzed so as to illustrate the approach. The main achievement of this communication is the possibility of clearly distinguishing between them in our representation space, something that is rather difficult otherwise.Instituto de Física La Plata2007-10-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/126151enginfo:eu-repo/semantics/altIdentifier/url/https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.99.154102info:eu-repo/semantics/altIdentifier/issn/0031-9007info:eu-repo/semantics/altIdentifier/issn/1079-7114info:eu-repo/semantics/altIdentifier/pmid/17995170info:eu-repo/semantics/altIdentifier/doi/10.1103/physrevlett.99.154102info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:30:22Zoai:sedici.unlp.edu.ar:10915/126151Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:30:23.069SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Distinguishing noise from chaos |
title |
Distinguishing noise from chaos |
spellingShingle |
Distinguishing noise from chaos Rosso, Osvaldo A. Física Ciencias Exactas Chaotic systems Entropy (information theory) Representation space |
title_short |
Distinguishing noise from chaos |
title_full |
Distinguishing noise from chaos |
title_fullStr |
Distinguishing noise from chaos |
title_full_unstemmed |
Distinguishing noise from chaos |
title_sort |
Distinguishing noise from chaos |
dc.creator.none.fl_str_mv |
Rosso, Osvaldo A. Larrondo, Hilda Ángela Martín, María Teresa Plastino, Ángel Luis Fuentes, Miguel A. |
author |
Rosso, Osvaldo A. |
author_facet |
Rosso, Osvaldo A. Larrondo, Hilda Ángela Martín, María Teresa Plastino, Ángel Luis Fuentes, Miguel A. |
author_role |
author |
author2 |
Larrondo, Hilda Ángela Martín, María Teresa Plastino, Ángel Luis Fuentes, Miguel A. |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
Física Ciencias Exactas Chaotic systems Entropy (information theory) Representation space |
topic |
Física Ciencias Exactas Chaotic systems Entropy (information theory) Representation space |
dc.description.none.fl_txt_mv |
Chaotic systems share with stochastic processes several properties that make them almost undistinguishable. In this communication we introduce a representation space, to be called the complexity-entropy causality plane. Its horizontal and vertical axis are suitable functionals of the pertinent probability distribution, namely, the entropy of the system and an appropriate statistical complexity measure, respectively. These two functionals are evaluated using the Bandt-Pompe recipe to assign a probability distribution function to the time series generated by the system. Several well-known model-generated time series, usually regarded as being of either stochastic or chaotic nature, are analyzed so as to illustrate the approach. The main achievement of this communication is the possibility of clearly distinguishing between them in our representation space, something that is rather difficult otherwise. Instituto de Física La Plata |
description |
Chaotic systems share with stochastic processes several properties that make them almost undistinguishable. In this communication we introduce a representation space, to be called the complexity-entropy causality plane. Its horizontal and vertical axis are suitable functionals of the pertinent probability distribution, namely, the entropy of the system and an appropriate statistical complexity measure, respectively. These two functionals are evaluated using the Bandt-Pompe recipe to assign a probability distribution function to the time series generated by the system. Several well-known model-generated time series, usually regarded as being of either stochastic or chaotic nature, are analyzed so as to illustrate the approach. The main achievement of this communication is the possibility of clearly distinguishing between them in our representation space, something that is rather difficult otherwise. |
publishDate |
2007 |
dc.date.none.fl_str_mv |
2007-10-12 |
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/10915/126151 |
url |
http://sedici.unlp.edu.ar/handle/10915/126151 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.99.154102 info:eu-repo/semantics/altIdentifier/issn/0031-9007 info:eu-repo/semantics/altIdentifier/issn/1079-7114 info:eu-repo/semantics/altIdentifier/pmid/17995170 info:eu-repo/semantics/altIdentifier/doi/10.1103/physrevlett.99.154102 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International (CC BY 4.0) |
eu_rights_str_mv |
openAccess |
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http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International (CC BY 4.0) |
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application/pdf |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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