Wavelet entropy of stochastic processes

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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Detalles Bibliográficos
Publicado: 2007
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:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v379_n2_p503_Zunino
http://hdl.handle.net/20.500.12110/paper_03784371_v379_n2_p503_Zunino
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_03784371_v379_n2_p503_Zunino
record_format dspace
spelling paper:paper_03784371_v379_n2_p503_Zunino2023-06-08T15:40:08Z Wavelet entropy of stochastic processes 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. 2007 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v379_n2_p503_Zunino 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
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.
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
publishDate 2007
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v379_n2_p503_Zunino
http://hdl.handle.net/20.500.12110/paper_03784371_v379_n2_p503_Zunino
_version_ 1768543564626657280

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