Wavelet entropy of stochastic processes
- Autores
- Zunino, Luciano José; Pérez, Darío Gabriel; Garavaglia, Mario José; Rosso, O. A.
- Año de publicación
- 2007
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- 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 () and fractional Brownian motion () are assessed. We find out that the NTWS family performs better as a characterization method for these stochastic processes.
Centro de Investigaciones Ópticas
Facultad de Ingeniería
Facultad de Ciencias Exactas - Materia
-
Física
Wavelet analysis
Wavelet entropy
Fractional
Brownian motion
Fractional Gaussian noise
α-parameter - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/131070
Ver los metadatos del registro completo
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Wavelet entropy of stochastic processesZunino, Luciano JoséPérez, Darío GabrielGaravaglia, Mario JoséRosso, O. A.FísicaWavelet analysisWavelet entropyFractionalBrownian motionFractional Gaussian noiseα-parameterWe 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 (<math><mo is="true">-</mo><mn is="true">1</mn><mo is="true"><</mo><mi is="true">α</mi><mo is="true"><</mo><mspace width="0.33em" is="true"></mspace><mn is="true">1</mn></math>) and fractional Brownian motion (<math><mn is="true">1</mn><mo is="true"><</mo><mi is="true">α</mi><mo is="true"><</mo><mspace width="0.33em" is="true"></mspace><mn is="true">3</mn></math>) are assessed. We find out that the NTWS family performs better as a characterization method for these stochastic processes.Centro de Investigaciones ÓpticasFacultad de IngenieríaFacultad de Ciencias Exactas2007info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf503-512http://sedici.unlp.edu.ar/handle/10915/131070enginfo:eu-repo/semantics/altIdentifier/issn/0378-4371info:eu-repo/semantics/altIdentifier/arxiv/physics/0603144info:eu-repo/semantics/altIdentifier/doi/10.1016/j.physa.2006.12.057info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T11:03:23Zoai:sedici.unlp.edu.ar:10915/131070Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 11:03:23.472SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
Wavelet entropy of stochastic processes |
| title |
Wavelet entropy of stochastic processes |
| spellingShingle |
Wavelet entropy of stochastic processes Zunino, Luciano José Física Wavelet analysis Wavelet entropy Fractional Brownian motion Fractional Gaussian noise α-parameter |
| 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 |
| dc.creator.none.fl_str_mv |
Zunino, Luciano José Pérez, Darío Gabriel Garavaglia, Mario José Rosso, O. A. |
| author |
Zunino, Luciano José |
| author_facet |
Zunino, Luciano José Pérez, Darío Gabriel Garavaglia, Mario José Rosso, O. A. |
| author_role |
author |
| author2 |
Pérez, Darío Gabriel Garavaglia, Mario José Rosso, O. A. |
| author2_role |
author author author |
| dc.subject.none.fl_str_mv |
Física Wavelet analysis Wavelet entropy Fractional Brownian motion Fractional Gaussian noise α-parameter |
| topic |
Física Wavelet analysis Wavelet entropy Fractional Brownian motion Fractional Gaussian noise α-parameter |
| dc.description.none.fl_txt_mv |
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 (<math><mo is="true">-</mo><mn is="true">1</mn><mo is="true"><</mo><mi is="true">α</mi><mo is="true"><</mo><mspace width="0.33em" is="true"></mspace><mn is="true">1</mn></math>) and fractional Brownian motion (<math><mn is="true">1</mn><mo is="true"><</mo><mi is="true">α</mi><mo is="true"><</mo><mspace width="0.33em" is="true"></mspace><mn is="true">3</mn></math>) are assessed. We find out that the NTWS family performs better as a characterization method for these stochastic processes. Centro de Investigaciones Ópticas Facultad de Ingeniería Facultad de Ciencias Exactas |
| 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 (<math><mo is="true">-</mo><mn is="true">1</mn><mo is="true"><</mo><mi is="true">α</mi><mo is="true"><</mo><mspace width="0.33em" is="true"></mspace><mn is="true">1</mn></math>) and fractional Brownian motion (<math><mn is="true">1</mn><mo is="true"><</mo><mi is="true">α</mi><mo is="true"><</mo><mspace width="0.33em" is="true"></mspace><mn is="true">3</mn></math>) are assessed. We find out that the NTWS family performs better as a characterization method for these stochastic processes. |
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2007 |
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2007 |
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eng |
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eng |
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