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
Autores: Zunino, Luciano José, Pérez, D. G., Garavaglia, Mario Jose, Rosso, Osvaldo Aníbal
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2007
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/155228
Acceso en línea:http://hdl.handle.net/11336/155228
Access Level:acceso abierto
Palabra clave:Wavelet analysis
Wavelet entropy
Fractional Brownian motion
Fractional Gaussian noise
Parameter
https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
Descripción
Sumario: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. Schu¨rmann, E. Bas-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 Lucena [Physica A 357(1) (2005) 71–78]. In order to understand their advantages and disadvantages, exact results obtained for fractional Gaussian noise (1oao 1) and fractional Brownian motion (1oao 3) are assessed. We find out that the NTWS family performs better as a characterization method for these stochastic processes.