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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Detalhes bibliográficos
Autores: Zunino, Luciano José; Pérez, D. G.; Garavaglia, Mario Jose; Rosso, Osvaldo Aníbal
Tipo de documento: Artigo
Estado:Published version
Data de publicação:2007
País:Argentina
Recursos:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositório:CONICET Digital (CONICET)
Idioma:Inglês
OAI Identifier:oai:ri.conicet.gov.ar:11336/155228
Acesso em linha:http://hdl.handle.net/11336/155228
Nível de acesso:Acesso aberto
Palavra-chave:Wavelet analysis
Wavelet entropy
Fractional Brownian motion
Fractional Gaussian noise
Parameter
https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
Descrição
Resumo: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.