{"id":29491,"date":"2018-03-09T09:22:38","date_gmt":"2018-03-09T09:22:38","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/extraccion-de-caractera%c2%adsticas-empleando-tecnicas-de-optimizacion-aleatoria\/"},"modified":"2018-03-09T09:22:38","modified_gmt":"2018-03-09T09:22:38","slug":"extraccion-de-caractera%c2%adsticas-empleando-tecnicas-de-optimizacion-aleatoria","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/politecnica-de-valencia\/extraccion-de-caractera%c2%adsticas-empleando-tecnicas-de-optimizacion-aleatoria\/","title":{"rendered":"Extracci\u00f3n de caracter\u00edsticas empleando t\u00e9cnicas de optimizaci\u00f3n aleatoria"},"content":{"rendered":"<h2>Tesis doctoral de <strong> Alberto Jos\u00e9 P\u00e9rez Jim\u00e9nez <\/strong><\/h2>\n<p>Una de las etapas m\u00e1s relevantes de un sistema de reconocimiento autom\u00e1tico basado en m\u00e9todos estad\u00edsticos es la etapa de extracci\u00f3n de caracter\u00edsticas. esta etapa se encarga de recodificar la representaci\u00f3n original de los objetos con una doble intenci\u00f3n: por un lado facilitar la tarea a los algoritmos de clasificaci\u00f3n, y por otro reducir la complejidad espacial y temporal de \u00e9stos.  las nuevas caracter\u00edsticas que recodificar\u00e1n a los objetos pueden obtenerse mediante transformaciones lineales o no lineales de las caracter\u00edsticas originales. El presente trabajo presenta diferentes m\u00e9todos de extracci\u00f3n de caracter\u00edsticas que hacen uso de m\u00e9todos de optimizaci\u00f3n aleatoria para obtener los coeficientes de dichas transformaciones. Estos m\u00e9todos tratar\u00e1n de obtener una nueva codificaci\u00f3n de los objetos de tal modo que se optimicen la precisi\u00f3n (tasa de aciertos) de los clasificadores dise\u00f1ados sobre el nuevo espacio de representaci\u00f3n generado.  debido por una parte a los grandes espacios de b\u00fasqueda que se generar\u00e1n, especialmente si partimos de un n\u00famero elevado de caracter\u00edsticas originales o hacemos uso de transformaciones no lineales. Y por otra parte, a la complejidad de la funci\u00f3n a optimizar (la tasa de aciertos), el uso de m\u00e9todos de optimizaci\u00f3n basados en el c\u00e1lculo (ascenso por gradiente, derivaci\u00f3n,..) Ser\u00e1 complejos, o incluso imposible si empleamos clasificadores no param\u00e9tricos (por ejemplo, k-vecinos m\u00e1s pr\u00f3ximos). Por estos motivos proponemos hacer uso de m\u00e9todos de optimizaci\u00f3n aleatoria (algoritmo gen\u00e9ticos, hill climbing,&#8230;) Para obtener los coeficientes de las transformaciones.  el planteamiento propuesto se emplear\u00e1 tanto para realizar extracci\u00f3n lineal como extracci\u00f3n no lineal de caracter\u00edsticas. En el caso de la extracci\u00f3n no lineal se emplear\u00e1 una nueva familia de transformaciones presentadas en esta tesis: las proyecciones radiales. Se trata de una familia de transform<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Extracci\u00f3n de caracter\u00edsticas empleando t\u00e9cnicas de optimizaci\u00f3n aleatoria<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Extracci\u00f3n de caracter\u00edsticas empleando t\u00e9cnicas de optimizaci\u00f3n aleatoria <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Alberto Jos\u00e9 P\u00e9rez Jim\u00e9nez <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Polit\u00e9cnica de Valencia<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 30\/03\/2004<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Juan  Carlos Perez Cortes<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: enrique Vidal ruiz <\/li>\n<li>Jos\u00e9 Oncina carratal\u00e1 (vocal)<\/li>\n<li>francesc josep Ferri rabasa (vocal)<\/li>\n<li>petia Ivanova radeva (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Alberto Jos\u00e9 P\u00e9rez Jim\u00e9nez Una de las etapas m\u00e1s relevantes de un sistema de reconocimiento autom\u00e1tico basado [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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