¹University of Shahid Chamran, Faculty of Mathematics and Computer Science, Department of Statistics, Ahvaz, Iran. Assistant Professor. Email: b.mansouri@scu.ac.ir
²University of Shahid Chamran, Faculty of Mathematics and Computer Science, Department of Statistics, Ahvaz, Iran. Professor. Email: chinipardaz_r@scu.ac.ir

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.

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