Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach

Autores
Rosso, O. A.; Zunino, Luciano José; Pérez, Darío G.; Figliola, Alejandra; Larrondo, Hilda A.; Garavaglia, Mario José; Martín, María Teresa; Plastino, Ángel Luis
Año de publicación
2007
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
By recourse to appropriate information theory quantifiers (normalized Shannon entropy and Martin-Plastino-Rosso intensive statistical complexity measure), we revisit the characterization of Gaussian self-similar stochastic processes from a Bandt-Pompe viewpoint. We show that the ensuing approach exhibits considerable advantages with respect to other treatments. In particular, clear quantifiers gaps are found in the transition between the continuous processes and their associated noises.
Centro de Investigaciones Ópticas
Instituto de Física La Plata
Facultad de Ingeniería
Materia
Física
Statistical physics
Data mining
Time series
Continuous-time stochastic process
Gaussian
Shannon's source coding theorem
Measure (mathematics)
Statistical complexity
Mathematics
Information theory
Stochastic process
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:10915/126170
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/126170
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approachRosso, O. A.Zunino, Luciano JoséPérez, Darío G.Figliola, AlejandraLarrondo, Hilda A.Garavaglia, Mario JoséMartín, María TeresaPlastino, Ángel LuisFísicaStatistical physicsData miningTime seriesContinuous-time stochastic processGaussianShannon's source coding theoremMeasure (mathematics)Statistical complexityMathematicsInformation theoryStochastic processBy recourse to appropriate information theory quantifiers (normalized Shannon entropy and Martin-Plastino-Rosso intensive statistical complexity measure), we revisit the characterization of Gaussian self-similar stochastic processes from a Bandt-Pompe viewpoint. We show that the ensuing approach exhibits considerable advantages with respect to other treatments. In particular, clear quantifiers gaps are found in the transition between the continuous processes and their associated noises.Centro de Investigaciones ÓpticasInstituto de Física La PlataFacultad de Ingeniería2007-12-12info: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/10915/126170enginfo:eu-repo/semantics/altIdentifier/issn/1539-3755info:eu-repo/semantics/altIdentifier/issn/1550-2376info:eu-repo/semantics/altIdentifier/doi/10.1103/physreve.76.061114info: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:UNLP2025-10-22T17:11:17Zoai:sedici.unlp.edu.ar:10915/126170Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 17:11:17.331SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach
title Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach
spellingShingle Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach
Rosso, O. A.
Física
Statistical physics
Data mining
Time series
Continuous-time stochastic process
Gaussian
Shannon's source coding theorem
Measure (mathematics)
Statistical complexity
Mathematics
Information theory
Stochastic process
title_short Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach
title_full Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach
title_fullStr Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach
title_full_unstemmed Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach
title_sort Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach
dc.creator.none.fl_str_mv Rosso, O. A.
Zunino, Luciano José
Pérez, Darío G.
Figliola, Alejandra
Larrondo, Hilda A.
Garavaglia, Mario José
Martín, María Teresa
Plastino, Ángel Luis
author Rosso, O. A.
author_facet Rosso, O. A.
Zunino, Luciano José
Pérez, Darío G.
Figliola, Alejandra
Larrondo, Hilda A.
Garavaglia, Mario José
Martín, María Teresa
Plastino, Ángel Luis
author_role author
author2 Zunino, Luciano José
Pérez, Darío G.
Figliola, Alejandra
Larrondo, Hilda A.
Garavaglia, Mario José
Martín, María Teresa
Plastino, Ángel Luis
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Física
Statistical physics
Data mining
Time series
Continuous-time stochastic process
Gaussian
Shannon's source coding theorem
Measure (mathematics)
Statistical complexity
Mathematics
Information theory
Stochastic process
topic Física
Statistical physics
Data mining
Time series
Continuous-time stochastic process
Gaussian
Shannon's source coding theorem
Measure (mathematics)
Statistical complexity
Mathematics
Information theory
Stochastic process
dc.description.none.fl_txt_mv By recourse to appropriate information theory quantifiers (normalized Shannon entropy and Martin-Plastino-Rosso intensive statistical complexity measure), we revisit the characterization of Gaussian self-similar stochastic processes from a Bandt-Pompe viewpoint. We show that the ensuing approach exhibits considerable advantages with respect to other treatments. In particular, clear quantifiers gaps are found in the transition between the continuous processes and their associated noises.
Centro de Investigaciones Ópticas
Instituto de Física La Plata
Facultad de Ingeniería
description By recourse to appropriate information theory quantifiers (normalized Shannon entropy and Martin-Plastino-Rosso intensive statistical complexity measure), we revisit the characterization of Gaussian self-similar stochastic processes from a Bandt-Pompe viewpoint. We show that the ensuing approach exhibits considerable advantages with respect to other treatments. In particular, clear quantifiers gaps are found in the transition between the continuous processes and their associated noises.
publishDate 2007
dc.date.none.fl_str_mv 2007-12-12
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/10915/126170
url http://sedici.unlp.edu.ar/handle/10915/126170
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1539-3755
info:eu-repo/semantics/altIdentifier/issn/1550-2376
info:eu-repo/semantics/altIdentifier/doi/10.1103/physreve.76.061114
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
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 12.982451

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