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Revista Colombiana de Estadística

Print version ISSN 0120-1751

Rev.Colomb.Estad. vol.39 no.1 Bogotá Jan./June 2016


Asymptotic Information Measures Discrimination of Non-Stationary Time Series Based on Wavelet Domain

Discriminacion de medidas de información asintótica de series de tiempo no estacionarias basadas en dominio wavelet


1University of Shahid Chamran, Faculty of Mathematics and Computer Science, Department of Statistics, Ahvaz, Iran. Assistant Professor. Email:
2University of Shahid Chamran, Faculty of Mathematics and Computer Science, Department of Statistics, Ahvaz, Iran. Professor. Email:


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.

Key words: Chernoff information, discrimination, evolutionary wavelet spectrum, Kullback - Leibler information, locally stationary wavelet processes, seismic data.


Este artículo se refiere al problema de discriminación entre dos clases de series de tiempo estacionarias locales basadas en información de discriminación mínima. Se consideran las señales observadas como realizaciones de procesos wavelet estacionarios locales (LSW, por sus siglas en inglés) gausianos. La información de discriminación Kullback - Leibler asintótica y la información de discriminación de Chernoff se desarrollan como criterios discriminantes para procesos LSW. El estudio de simulación mostró que el procedimiento propuesto se desempeña tan bien como otros procedimientos y en algunos casos mejor que otros métodos de clasificación. Aplicaciones a la clasificación de datos sísmicos muestran la utilidad de los criterios discriminantes propuestos.

Palabras clave: LaTeX Datos sísmicos, discriminación, espectros wavelet evolucionariosinformación de Chernoff, información de Kullback-Leibler, procesos wavelet estacionarios locales.

Texto completo disponible en PDF


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[Recibido en junio de 2014. Aceptado en marzo de 2015]

Este artículo se puede citar en LaTeX utilizando la siguiente referencia bibliográfica de BibTeX:

    AUTHOR  = {Mansouri, Behzad and Chinipardaz, Rahim},
    TITLE   = {{Asymptotic Information Measures Discrimination of Non-Stationary Time Series Based on Wavelet Domain}},
    JOURNAL = {Revista Colombiana de Estadística},
    YEAR    = {2016},
    volume  = {39},
    number  = {1},
    pages   = {81-95}