Wavelet entropy of stochastic processes

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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, III. Wavelet packe...

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Autores principales: Zunino, L., Pérez, D.G., Garavaglia, M., Rosso, O.A.
Formato: JOUR
Materias:
α-parameter
Fractional Brownian motion
Fractional Gaussian noise
Wavelet analysis
Wavelet entropy
Electroencephalography
Frequency domain analysis
Function evaluation
Gaussian noise (electronic)
Time domain analysis
Brownian movement
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_03784371_v379_n2_p503_Zunino
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Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
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spelling todo:paper_03784371_v379_n2_p503_Zunino2023-10-03T15:32:50Z Wavelet entropy of stochastic processes Zunino, L. Pérez, D.G. Garavaglia, M. Rosso, O.A. α-parameter Fractional Brownian motion Fractional Gaussian noise Wavelet analysis Wavelet entropy Electroencephalography Frequency domain analysis Function evaluation Gaussian noise (electronic) Time domain analysis Wavelet analysis α-parameter Fractional Brownian motion Fractional Gaussian noise Wavelet entropy Brownian movement 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, III. 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. Schürmann, E. Başar, 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 Lucena [Physica A 357(1) (2005) 71-78]. In order to understand their advantages and disadvantages, exact results obtained for fractional Gaussian noise (- 1 < α < 1) and fractional Brownian motion (1 < α < 3) are assessed. We find out that the NTWS family performs better as a characterization method for these stochastic processes. © 2007 Elsevier B.V. All rights reserved. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03784371_v379_n2_p503_Zunino
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic α-parameter
Fractional Brownian motion
Fractional Gaussian noise
Wavelet analysis
Wavelet entropy
Electroencephalography
Frequency domain analysis
Function evaluation
Gaussian noise (electronic)
Time domain analysis
Wavelet analysis
α-parameter
Fractional Brownian motion
Fractional Gaussian noise
Wavelet entropy
Brownian movement
spellingShingle α-parameter
Fractional Brownian motion
Fractional Gaussian noise
Wavelet analysis
Wavelet entropy
Electroencephalography
Frequency domain analysis
Function evaluation
Gaussian noise (electronic)
Time domain analysis
Wavelet analysis
α-parameter
Fractional Brownian motion
Fractional Gaussian noise
Wavelet entropy
Brownian movement
Zunino, L.
Pérez, D.G.
Garavaglia, M.
Rosso, O.A.
Wavelet entropy of stochastic processes
topic_facet α-parameter
Fractional Brownian motion
Fractional Gaussian noise
Wavelet analysis
Wavelet entropy
Electroencephalography
Frequency domain analysis
Function evaluation
Gaussian noise (electronic)
Time domain analysis
Wavelet analysis
α-parameter
Fractional Brownian motion
Fractional Gaussian noise
Wavelet entropy
Brownian movement
description 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, III. 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. Schürmann, E. Başar, 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 Lucena [Physica A 357(1) (2005) 71-78]. In order to understand their advantages and disadvantages, exact results obtained for fractional Gaussian noise (- 1 < α < 1) and fractional Brownian motion (1 < α < 3) are assessed. We find out that the NTWS family performs better as a characterization method for these stochastic processes. © 2007 Elsevier B.V. All rights reserved.
format JOUR
author Zunino, L.
Pérez, D.G.
Garavaglia, M.
Rosso, O.A.
author_facet Zunino, L.
Pérez, D.G.
Garavaglia, M.
Rosso, O.A.
author_sort Zunino, L.
title Wavelet entropy of stochastic processes
title_short Wavelet entropy of stochastic processes
title_full Wavelet entropy of stochastic processes
title_fullStr Wavelet entropy of stochastic processes
title_full_unstemmed Wavelet entropy of stochastic processes
title_sort wavelet entropy of stochastic processes
url http://hdl.handle.net/20.500.12110/paper_03784371_v379_n2_p503_Zunino
work_keys_str_mv AT zuninol waveletentropyofstochasticprocesses
AT perezdg waveletentropyofstochasticprocesses
AT garavagliam waveletentropyofstochasticprocesses
AT rossooa waveletentropyofstochasticprocesses
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