CIOP   05384
CENTRO DE INVESTIGACIONES OPTICAS
Unidad Ejecutora - UE
artículos
Título:
Characterization of Gaussian self-similar stochastic processes using wavelet-based informational tools.
Autor/es:
L. ZUNINO, D. G. PÉREZ, M. T. MARTIN, A. PLASTINO, M. GARAVAGLIA AND O. A. ROSSO
Revista:
PHYSICAL REVIEW E - STATISTICAL PHYSICS, PLASMAS, FLUIDS AND RELATED INTERDISCIPLINARY TOPICS
Referencias:
Año: 2006 vol. 75
ISSN:
1063-651X
Resumen:
Efficient tools to characterize stochastic processes are discussed. Quantifiers originally proposed within the
framework of information theory, like entropy and statistical complexity, are translated into wavelet language,
which renders the above quantifiers into tools that exhibit the important "localization" advantages provided by
wavelet theory. Two important and popular stochastic processes, fractional Brownian motion and fractional
Gaussian noise, are studied using these wavelet-based informational tools. Exact analytical expressions are
obtained for the wavelet probability distribution. Finally, numerical simulations are used to validate our ana-lytical
results.
DOI: 10.1103/PhysRevE.75.021115 PACS numbers: 02.50.Ey10.1103/PhysRevE.75.021115 PACS numbers: 02.50.Ey