{"id":32691,"date":"1997-01-01T00:00:00","date_gmt":"1997-01-01T00:00:00","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/redes-neuronales-hibridas-variantes-constructivas-y-probabilisticas-aplicadas-a-la-clasificacion-de-patrones\/"},"modified":"1997-01-01T00:00:00","modified_gmt":"1997-01-01T00:00:00","slug":"redes-neuronales-hibridas-variantes-constructivas-y-probabilisticas-aplicadas-a-la-clasificacion-de-patrones","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/fisica\/redes-neuronales-hibridas-variantes-constructivas-y-probabilisticas-aplicadas-a-la-clasificacion-de-patrones\/","title":{"rendered":"Redes neuronales hibridas: variantes constructivas y probabilisticas aplicadas a la clasificacion de patrones."},"content":{"rendered":"<h2>Tesis doctoral de <strong> Jos\u00e9 Luis Alba Castro <\/strong><\/h2>\n<p>Esta tesis propone nuevas soluciones constructivas al problema del entrenamiento de una red neuronal hibrida aplicada a la clasificacion de patrones. El trabajo se plantea desde dos perspectivas distintas: una conexionista utilizando tecnicas fundamentadas en algoritmos propios del campo de las redes neuronales, y otra probabilistica, con soluciones mas afines al campo de la estadistica. Cada uno de estos dos planteamientos deriva en una arquitectura constructiva que es capaz de generar un clasificador de prestaciones comparables a modelos ampliamente difundidos, como el perceptron multicapa (mlp), las redes con funciones de base radial (rbf) o los clasificadores basados en la regla de los k vecinos mas proximos (k-nn).  ambas arquitecturas constructivas incorporan instrumentos para controlar la complejidad del modelo con el proposito de mantener una generalizacion adecuada. El control de la complejidad sirve asimismo, como una forma de detener el proceso de entrenamiento.  a lo largo de la tesis se muestra un conjunto de experimentos con datos generados artificialmente que reflejan las prestaciones de ambas redes neuronales y permiten evaluar la influencia, en el crecimiento y en la tasa de error, de los distintos parametros incorporados en los algoritmos. Las pruebas realizadas con datos procedentes de aplicaciones reales corroboran las conclusiones extraidas a partir de las pruebas artificiales y de los teoricos que fundamentan los algoritmos.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Redes neuronales hibridas: variantes constructivas y probabilisticas aplicadas a la clasificacion de patrones.<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Redes neuronales hibridas: variantes constructivas y probabilisticas aplicadas a la clasificacion de patrones. <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Jos\u00e9 Luis Alba Castro <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Vigo<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 01\/01\/1997<\/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>Domingo Docampo Amoedo<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: Juan  Ram\u00f3n Vidal Roman\u00ed <\/li>\n<li>Joan Cabestany I Moncus\u00ed (vocal)<\/li>\n<li>Wenceslao Gonz\u00e1lez Manteiga (vocal)<\/li>\n<li>Jes\u00fas Cid Sueiro (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Jos\u00e9 Luis Alba Castro Esta tesis propone nuevas soluciones constructivas al problema del entrenamiento de una red [&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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