Journal
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
Volume 379, Issue 2, Pages 503-512Publisher
ELSEVIER
DOI: 10.1016/j.physa.2006.12.057
Keywords
wavelet analysis; wavelet entropy; fractional Brownian motion; fractional Gaussian noise; alpha-parameter
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We compare two different definitions for the wavelet entropy associated to stochastic processes. The first one, the normalized total wavelet entropy (NTWS) family [S. Blanco, A. Figliola, R.Q. Quiroga, O.A. Rosso, E. Serrano, Time-frequency analysis of electroencephalogram series, Ill. Wavelet packets and information cost function, Phys. Rev. E 57 (1998) 932-940; O.A. Rosso, S. Blanco, J. Yordanova, V. Kolev, A. Figliola, M. Schurmann, E. Ba ar, Wavelet entropy: a new tool for analysis of short duration brain electrical signals, J. Neurosci. Method 105 (2001) 65-75] and a second introduced by Tavares and Lueena [Physica A 357(1) (2005) 71-78]. In order to understand their advantages and disadvantages, exact results obtained for fractional Gaussian noise (-1 < 1) and fractional Brownian motion (1 < 3) are assessed. We find out that the NTWS family performs better as a characterization method for these stochastic processes. (C) 2007 Elsevier BN. All rights reserved.
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