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

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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 exh...

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Detalles Bibliográficos
Autores principales: Rosso, O. A., Zunino, Luciano José, Pérez, Darío G., Figliola, Alejandra, Larrondo, Hilda A., Garavaglia, Mario José, Martín, María Teresa, Plastino, Ángel Luis
Formato: Articulo
Lenguaje:Inglés
Publicado: 2007
Materias:
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
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/126170
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-126170
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
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
spellingShingle 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
Rosso, O. A.
Zunino, Luciano José
Pérez, Darío G.
Figliola, Alejandra
Larrondo, Hilda A.
Garavaglia, Mario José
Martín, María Teresa
Plastino, Ángel Luis
Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach
topic_facet 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
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.
format Articulo
Articulo
author Rosso, O. A.
Zunino, Luciano José
Pérez, Darío G.
Figliola, Alejandra
Larrondo, Hilda A.
Garavaglia, Mario José
Martín, María Teresa
Plastino, Ángel Luis
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_sort Rosso, O. A.
title Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach
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
publishDate 2007
url http://sedici.unlp.edu.ar/handle/10915/126170
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