{"id":26003,"date":"2018-03-09T09:17:37","date_gmt":"2018-03-09T09:17:37","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/control-de-la-complejidad-en-modelos-no-lineales\/"},"modified":"2018-03-09T09:17:37","modified_gmt":"2018-03-09T09:17:37","slug":"control-de-la-complejidad-en-modelos-no-lineales","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/matematicas\/control-de-la-complejidad-en-modelos-no-lineales\/","title":{"rendered":"Control de la complejidad en modelos no lineales"},"content":{"rendered":"<h2>Tesis doctoral de <strong> Elisa Guerrero V\u00e1zquez <\/strong><\/h2>\n<p>El aprendizaje mediante ejemplos constituye una de las \u00e1reas de investigaci\u00f3n m\u00e1s importantes dentro del campo de la inteligencia artificial. Una posible formalizaci\u00f3n del aprendizaje mediante ejemplos es suponer la existencia de una funci\u00f3n subyacente que represente al conjunto de observaciones, y que sea capaz de generalizar. La capacidad de generalizaci\u00f3n se define en esta tesis mediante el error cuadr\u00e1tico sobre la distribuci\u00f3n completa que define el sistema estoc\u00e1stico, y se denominar\u00e1 riesgo de predicci\u00f3n. dentro de este marco general la potencia de representaci\u00f3n de los modelos dados constituye una parte fundamental de estudio.  los modelos no lineales se caracterizan por su gran flexibilidad para representar cualquier dependencia subyacente a partir de un conjunto de datos. Dentro de los sistemas no lineales, las redes neuronales constituyen una de las clases de funciones aproximadoras m\u00e1s ampliamente utilizadas dado que son aproximadores universales. El coste de su flexibilidad es la presencia de un n\u00famero importante de par\u00e1metros cuyos valores han de ser correctamente establecidos, tanto en la elecci\u00f3n de la arquitectura como en la especificaci\u00f3n de la dimensi\u00f3n y complejidad.  al problema de elegir de forma \u00f3ptima la complejidad de un modelo se le denomina selecci\u00f3n de modelos. El problema de la selecci\u00f3n de modelos se basa en el principio de occam por el cual dadas dos hip\u00f3tesis con igual rendimiento, se debe elegir siempre la hip\u00f3tesis m\u00e1s simple.  existe una gran variedad de m\u00e9todos de selecci\u00f3n de modelos que utilizan un amplio rango de t\u00e9cnicas estad\u00edsticas e ilustran la gran creatividad de los investigadores por intentar resolver este problema desde distintas perspectivas. La mayor\u00eda de estos m\u00e9todos han sido dise\u00f1ados para modelos lineales y la utilizaci\u00f3n en modelos no lineales no est\u00e1 exenta de condiciones que reducen su aplicabilidad de forma notable en gran parte de las situaciones<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Control de la complejidad en modelos no lineales<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Control de la complejidad en modelos no lineales <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Elisa Guerrero V\u00e1zquez <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 C\u00e1diz<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 30\/09\/2003<\/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>Pedro Galindo Ria\u00f1o<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: gonzalo Joya caparros <\/li>\n<li> Jesus d\u00edas Mar\u00eda Jos\u00e9 del (vocal)<\/li>\n<li> Bernier villamor Jos\u00e9 Luis (vocal)<\/li>\n<li>joaqu\u00edn Pizarro tunquera (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Elisa Guerrero V\u00e1zquez El aprendizaje mediante ejemplos constituye una de las \u00e1reas de investigaci\u00f3n m\u00e1s importantes dentro [&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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