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

Authors: Rosso, O. A.; Zunino, Luciano José; Pérez, Darío G.; Figliola, Alejandra; Larrondo, Hilda A.; Garavaglia, Mario José; Martín, María Teresa; +1 Authors

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

Abstract

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.

Countries
Australia, Argentina
Keywords

Time series, Information theory, Continuous-time stochastic process, Shannon entropy, information theory quantifiers, Física, Stochastic process, Martín-Plastino-Rosso intensive statistical complexity, Shannon's source coding theorem, Gaussian, Statistical complexity, Bandt-Pompe, Statistical physics, Measure (mathematics), Data mining, Mathematics

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
57
Top 10%
Top 10%
Top 10%
Green
hybrid