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 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.
Rosso
O A
OA
Chaos & Biology Group, Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (UBA), Pabellón II, Ciudad Universitaria, 1428 Ciudad de Buenos Aires, Argentina. oarosso@fibertel.com.ar
Zunino
L
L
Pérez
D G
DG
Figliola
A
A
Larrondo
H A
HA
Garavaglia
M
M
Martín
M T
MT
Plastino
A
A