<?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>0123-921X</journal-id>
<journal-title><![CDATA[Tecnura]]></journal-title>
<abbrev-journal-title><![CDATA[Tecnura]]></abbrev-journal-title>
<issn>0123-921X</issn>
<publisher>
<publisher-name><![CDATA[Universidad Distrital Francisco José de Caldas]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0123-921X2017000400013</article-id>
<article-id pub-id-type="doi">10.14483/22487638.11708</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Modelación estadística de la textura del clutter marino en Matlab]]></article-title>
<article-title xml:lang="en"><![CDATA[Statistical modeling of the texture of sea clutter in Matlab]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Machado Fernández]]></surname>
<given-names><![CDATA[José Raúl]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pupo Hondal]]></surname>
<given-names><![CDATA[Raiko Israel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Tecnológica de La Habana José Antonio Echeverría (CUJAE)  ]]></institution>
<addr-line><![CDATA[La Habana ]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Tecnológica de La Habana José Antonio Echeverría (CUJAE)  ]]></institution>
<addr-line><![CDATA[La Habana ]]></addr-line>
<country>Cuba</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2017</year>
</pub-date>
<volume>21</volume>
<numero>54</numero>
<fpage>13</fpage>
<lpage>32</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0123-921X2017000400013&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0123-921X2017000400013&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0123-921X2017000400013&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Contexto: La modelación estadística de la señal interferente conocida como clutter marino se efectúa a través de dos componentes: uno de capilaridad y otro de textura. La distribución más utilizada para la textura es la gamma. No obstante, varios autores han defendido el uso alternativo de la inversa gamma y la inversa gaussiana.  Método: Con el objetivo de brindar un acceso fácil a la manipulación de los modelos y a la realización de comparaciones entre ellos, los autores del presente artículo simularon en Matlab las características principales de estas tres distribuciones. Adicionalmente, se agregó la distribución raíz gamma que sustituye a la gamma cuando se trabaja con muestras de amplitud. El método aplicado consistió en la revisión bibliográfica para encontrar las expresiones de cada uno de los parámetros modelados, y la posterior simulación computacional que permitió detectar errores ocasionales que surgen al consultar diferentes estudios.  Resultados:  Se creó una pequeña librería de simulación estocástica que incluye funciones de densidad y distribución, generación de variables aleatorias, estimación de parámetros y cálculo de momentos estadísticos, entre otros. Además, se elaboraron funciones informáticas complementarias que permitieron la validación por comparación con resultados dados por terceros y mediante la interacción de los diferentes componentes de la librería.  Conclusiones:  La librería creada habilita el uso de múltiples distribuciones, para la modelación del eco electromagnético de la superficie marina. Esto permitirá generar nuevos detectores de radar que se adapten a condiciones heterogéneas como las encontradas en las costas cubanas, donde alternan distintos niveles de profundidad, manglares, aguas salobres, islotes, vegetación acuática prominente, entre otras.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Context:  The statistical modeling of the interference signal known as sea clutter is achieved assuming the input results from the combination of two components: one for the speckle and another for the texture. The Gamma distribution is the more widely applied for the texture component. Nevertheless, several authors have defended the idea of using the Inverse Gamma and Inverse Gaussian instead.  Method: In order to provide an easy access to the handling of the models and the execution of comparisons between them, the authors of the current paper simulated in MATLAB the main characteristics of these distributions. In addition, the Root-Gamma model was also included because it replaces the Gamma distribution when samples are processed in the amplitude domain. The applied method consisted in a deep bibliography review for finding the corresponding expressions for each simulated model; the method also included additional computational simulations that allowed to identify occasional errors that were committed by different authors when characterizing the models.  Results: A small framework was created for stochastic simulation containing density and distribution functions, mechanisms for random variable generation, parameter estimation methods and statistical moment closed expressions, among others. Besides, complementary functions were prepared for guaranteeing the validation by comparison with results provided by third parties and through the interaction between the different components of the library.  Conclusions: The created library enables the use of multiple distributions for the modeling of the electromagnetic echo received from the sea surface. This will certainly motivate the creation of new radar detectors adapted to heterogeneous conditions such as the ones existing in Cuban coastal regions, where one may find different depth levels, mangrove swamps, brackish water, islets, prominent aquatic vegetation, among others.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[modelación estadística]]></kwd>
<kwd lng="es"><![CDATA[clutter marino]]></kwd>
<kwd lng="es"><![CDATA[textura del clutter]]></kwd>
<kwd lng="es"><![CDATA[distribución gamma]]></kwd>
<kwd lng="es"><![CDATA[distribución inversa gamma]]></kwd>
<kwd lng="es"><![CDATA[distribución inversa gaussiana]]></kwd>
<kwd lng="es"><![CDATA[distribución raíz gamma]]></kwd>
<kwd lng="en"><![CDATA[statistical modeling]]></kwd>
<kwd lng="en"><![CDATA[sea clutter]]></kwd>
<kwd lng="en"><![CDATA[texture of the clutter]]></kwd>
<kwd lng="en"><![CDATA[Gamma distribution]]></kwd>
<kwd lng="en"><![CDATA[Inverse Gamma distribution]]></kwd>
<kwd lng="en"><![CDATA[Inverse Gaussian distribution]]></kwd>
<kwd lng="en"><![CDATA[Root-Gamma distribution]]></kwd>
</kwd-group>
</article-meta>
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