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
Creator: Rosso, O. A.; Zunino, L.; Perez, D. G.; Figliola, A.; Larrondo, H. A.; Garavaglia, M.; Martin, M. T.; Plastino, A.
Relation: Physical Review E: Statistical, Nonlinear, and Soft Matter Physics Vol. 76, Issue 6
Publisher Link: http://dx.doi.org/10.1103/PhysRevE.76.061114
Publisher: American Physical Society
Resource Type: journal article
Date: 2007
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.
Subject: information theory quantifiers; Martín-Plastino-Rosso intensive statistical complexity; Shannon entropy; Bandt-Pompe
Identifier: http://hdl.handle.net/1959.13/33282
Identifier: uon:3147
Identifier: ISSN:1095-3787
Language: eng
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