Asymptotic Information Measures Discrimination of Non-Stationary Time Series Based on Wavelet Domain
This article is concerned with the problem of discrimination between two classes of locally stationary time series based on minimum discrimination information. We view the observed signals as realizations of Gaussian locally stationary wavelet (LSW) processes. The asymptotic Kullback - Leibler discr...
- Autores:
-
Mansouri, Behzad
Chinipa, Rahim
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2016
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/66524
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/66524
http://bdigital.unal.edu.co/67552/
- Palabra clave:
- 51 Matemáticas / Mathematics
31 Colecciones de estadística general / Statistics
Chernoff information
discrimination
evolutionary wavelet spectrum
Kullback - Leibler information
locally stationary wavelet processes
seismic data
Datos sísmicos
Discriminación
Espectros wavelet evolucionarios
Información de Chernoff
Información de Kullback-Leibler
Procesos wavelet estacionarios locales.
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | This article is concerned with the problem of discrimination between two classes of locally stationary time series based on minimum discrimination information. We view the observed signals as realizations of Gaussian locally stationary wavelet (LSW) processes. The asymptotic Kullback - Leibler discrimination information and Chernoff discrimination information are developed as discriminant criteria for LSW processes. The simulation study showed that our procedure performs as well as other procedures and in some cases better than some other classification methods. Applications to classifying real data show the usefulness of our discriminant criteria. |
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