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

• BEHZAD MANSOURI ^[1] ; RAHIM CHINIPARDAZ ^[1]
  1. [1] University of Shahid Chamran Faculty of Mathematics and Computer Science Department of Statistics
• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 39, Nº. 1, 2016, págs. 81-95
• Idioma: inglés
• DOI: 10.15446/rce.v39n1.55141
• Títulos paralelos:
  • Discriminacion de medidas de información asintótica de series de tiempo no estacionarias basadas en dominio wavelet
• Enlaces
  • Texto completo
• Resumen
  • español

    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.

  • English

    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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