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

By recourse to appropriate information theory quantifiers (normalized Shannon entropy and Martín-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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Autores principales: Rosso, O.A., Zunino, L., Pérez, D.G., Figliola, A., Larrondo, H.A., Garavaglia, M., Martín, M.T., Plastino, A.
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Acceso en línea:http://hdl.handle.net/20.500.12110/paper_15393755_v76_n6_p_Rosso
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spelling todo:paper_15393755_v76_n6_p_Rosso2023-10-03T16:22:17Z Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach Rosso, O.A. Zunino, L. Pérez, D.G. Figliola, A. Larrondo, H.A. Garavaglia, M. Martín, M.T. Plastino, A. Bandt-Pompe approach Gaussian self-similar stochastic processes Acoustic noise Characterization Entropy Information theory Statistical methods Random processes By recourse to appropriate information theory quantifiers (normalized Shannon entropy and Martín-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. © 2007 The American Physical Society. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_15393755_v76_n6_p_Rosso
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Bandt-Pompe approach
Gaussian self-similar stochastic processes
Acoustic noise
Characterization
Entropy
Information theory
Statistical methods
Random processes
spellingShingle Bandt-Pompe approach
Gaussian self-similar stochastic processes
Acoustic noise
Characterization
Entropy
Information theory
Statistical methods
Random processes
Rosso, O.A.
Zunino, L.
Pérez, D.G.
Figliola, A.
Larrondo, H.A.
Garavaglia, M.
Martín, M.T.
Plastino, A.
Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach
topic_facet Bandt-Pompe approach
Gaussian self-similar stochastic processes
Acoustic noise
Characterization
Entropy
Information theory
Statistical methods
Random processes
description By recourse to appropriate information theory quantifiers (normalized Shannon entropy and Martín-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. © 2007 The American Physical Society.
format JOUR
author Rosso, O.A.
Zunino, L.
Pérez, D.G.
Figliola, A.
Larrondo, H.A.
Garavaglia, M.
Martín, M.T.
Plastino, A.
author_facet Rosso, O.A.
Zunino, L.
Pérez, D.G.
Figliola, A.
Larrondo, H.A.
Garavaglia, M.
Martín, M.T.
Plastino, A.
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
url http://hdl.handle.net/20.500.12110/paper_15393755_v76_n6_p_Rosso
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