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

dc.creatorRosso, O. A.
dc.creatorZunino, Luciano José
dc.creatorPérez, Darío G.
dc.creatorFigliola, Alejandra
dc.creatorLarrondo, Hilda A.
dc.creatorGaravaglia, Mario José
dc.creatorMartín, María Teresa
dc.creatorPlastino, Ángel Luis
dc.date2007-12-12
dc.date2021-10-04T16:37:36Z
dc.date.accessioned2023-07-15T03:37:18Z
dc.date.available2023-07-15T03:37:18Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/126170
dc.identifierissn:1539-3755
dc.identifierissn:1550-2376
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7466410
dc.descriptionBy 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.
dc.descriptionCentro de Investigaciones Ópticas
dc.descriptionInstituto de Física La Plata
dc.descriptionFacultad de Ingeniería
dc.formatapplication/pdf
dc.languageen
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.subjectFísica
dc.subjectStatistical physics
dc.subjectData mining
dc.subjectTime series
dc.subjectContinuous-time stochastic process
dc.subjectGaussian
dc.subjectShannon's source coding theorem
dc.subjectMeasure (mathematics)
dc.subjectStatistical complexity
dc.subjectMathematics
dc.subjectInformation theory
dc.subjectStochastic process
dc.titleExtracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach
dc.typeArticulo
dc.typeArticulo


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