<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0120-1751</journal-id>
<journal-title><![CDATA[Revista Colombiana de Estadística]]></journal-title>
<abbrev-journal-title><![CDATA[Rev.Colomb.Estad.]]></abbrev-journal-title>
<issn>0120-1751</issn>
<publisher>
<publisher-name><![CDATA[Departamento de Estadística - Universidad Nacional de Colombia.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0120-17512016000100006</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Asymptotic Information Measures Discrimination of Non-Stationary Time Series Based on Wavelet Domain]]></article-title>
<article-title xml:lang="es"><![CDATA[Discriminacion de medidas de información asintótica de series de tiempo no estacionarias basadas en dominio wavelet]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[MANSOURI]]></surname>
<given-names><![CDATA[BEHZAD]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[CHINIPARDAZ]]></surname>
<given-names><![CDATA[RAHIM]]></given-names>
</name>
<xref ref-type="aff" rid="A02"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,University of Shahid Chamran Faculty of Mathematics and Computer Science Department of Statistics]]></institution>
<addr-line><![CDATA[Ahvaz ]]></addr-line>
<country>Iran</country>
</aff>
<aff id="A02">
<institution><![CDATA[,University of Shahid Chamran Faculty of Mathematics and Computer Science Department of Statistics]]></institution>
<addr-line><![CDATA[Ahvaz ]]></addr-line>
<country>Iran</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>01</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>01</month>
<year>2016</year>
</pub-date>
<volume>39</volume>
<numero>1</numero>
<fpage>81</fpage>
<lpage>95</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0120-17512016000100006&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0120-17512016000100006&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0120-17512016000100006&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[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.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[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.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Chernoff information]]></kwd>
<kwd lng="en"><![CDATA[discrimination]]></kwd>
<kwd lng="en"><![CDATA[evolutionary wavelet spectrum]]></kwd>
<kwd lng="en"><![CDATA[Kullback - Leibler information]]></kwd>
<kwd lng="en"><![CDATA[locally stationary wavelet processes]]></kwd>
<kwd lng="en"><![CDATA[seismic data]]></kwd>
<kwd lng="es"><![CDATA[LaTeX Datos sísmicos]]></kwd>
<kwd lng="es"><![CDATA[discriminación]]></kwd>
<kwd lng="es"><![CDATA[espectros wavelet evolucionariosinformación de Chernoff]]></kwd>
<kwd lng="es"><![CDATA[información de Kullback-Leibler]]></kwd>
<kwd lng="es"><![CDATA[procesos wavelet estacionarios locales]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[  <font size="2" face="verdana">      <p> <b> <font size="4">     <center> Asymptotic Information Measures Discrimination of Non-Stationary Time Series Based on Wavelet Domain </center> </font> </b> </p>      <p> <b> <font size="3">     <center> Discriminacion de medidas de informaci&oacute;n asint&oacute;tica de series de tiempo no estacionarias basadas en dominio wavelet </center> </font> </b> </p>      <p>     <center> BEHZAD MANSOURI<sup>1</sup>,  RAHIM CHINIPARDAZ<sup>2</sup> </center> </p>      <p> <sup>1</sup>University of Shahid Chamran, Faculty of Mathematics and Computer Science, Department of Statistics, Ahvaz, Iran. Assistant Professor. Email: <a href="mailto:b.mansouri@scu.ac.ir">b.mansouri@scu.ac.ir</a>     <br>  <sup>2</sup>University of Shahid Chamran, Faculty of Mathematics and Computer Science, Department of Statistics, Ahvaz, Iran. Professor. Email: <a href="mailto:chinipardaz_r@scu.ac.ir">chinipardaz_r@scu.ac.ir</a>     <br> </p>  <hr size="1">      ]]></body>
<body><![CDATA[<p> <b>     <center> Abstract </center> </b> </p>      <p> 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. </p>      <p> <b> Key words: </b> Chernoff information, discrimination, evolutionary wavelet spectrum, Kullback - Leibler information, locally stationary wavelet processes, seismic data. </p>  <hr size="1">      <p> <b>     <center> Resumen </center> </b> </p>      <p> Este art&iacute;culo se refiere al problema de discriminaci&oacute;n entre dos clases de series de tiempo estacionarias locales basadas en informaci&oacute;n de discriminaci&oacute;n m&iacute;nima. Se consideran las se&ntilde;ales observadas como realizaciones de procesos wavelet estacionarios locales (LSW, por sus siglas en ingl&eacute;s) gausianos. La informaci&oacute;n de discriminaci&oacute;n Kullback - Leibler asint&oacute;tica y la informaci&oacute;n de discriminaci&oacute;n de Chernoff se desarrollan como criterios discriminantes para procesos LSW. El estudio de simulaci&oacute;n mostr&oacute; que el procedimiento propuesto se desempe&ntilde;a tan bien como otros procedimientos y en algunos casos mejor que otros m&eacute;todos de clasificaci&oacute;n. Aplicaciones a la clasificaci&oacute;n de datos s&iacute;smicos muestran la utilidad de los criterios discriminantes propuestos. </p>      <p> <b> Palabras clave: </b> LaTeX  Datos s&iacute;smicos, discriminaci&oacute;n, espectros wavelet evolucionariosinformaci&oacute;n de Chernoff, informaci&oacute;n de Kullback-Leibler, procesos wavelet estacionarios locales. </p>  <hr size="1">      <p> Texto completo disponible en <a href="pdf/rce/v39n1/v39n1a06.pdf" target="_blank">PDF</a> </p>  <hr size="1">      <p> <b> <font size="3"> References </font> </b> </p>       ]]></body>
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<body><![CDATA[<br>  &nbsp;&nbsp;&nbsp; AUTHOR &nbsp;= {Mansouri, Behzad and Chinipardaz, Rahim},    <br>  &nbsp;&nbsp;&nbsp; TITLE &nbsp; = {{Asymptotic Information Measures Discrimination of Non-Stationary Time Series Based on Wavelet Domain}},    <br>  &nbsp;&nbsp;&nbsp; JOURNAL = {Revista Colombiana de Estad&iacute;stica},    <br> &nbsp;&nbsp;&nbsp; YEAR &nbsp;&nbsp; = {2016},    <br> &nbsp;&nbsp;&nbsp; volume &nbsp;= {39},    <br> &nbsp;&nbsp;&nbsp; number &nbsp;= {1},    <br> &nbsp;&nbsp;&nbsp; pages &nbsp; = {81-95}    <br> }</font></code>  <hr size="1"> </font>      ]]></body><back>
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