Robust Gamma-filter Using Support Vector Machines

This Letter presents a new approach to time-series modelling using the support vector machines (SVM). Although the g-filter can provide stability in several time-series models, the SVM is proposed here to provide robustness in the estimation of the g-filter coefficients. Examples in chaotic time-ser...

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Detalles Bibliográficos
Autores: Camps Valls, Gustavo, Martínez Ramón, Manel, Rojo-Álvarez, José Luis, Soria Olivas, Emilio
Tipo de recurso: artículo
Fecha de publicación:2009
País:España
Institución:Universidad Rey Juan Carlos
Repositorio:BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
OAI Identifier:oai:burjcdigital.urjc.es:10115/2490
Acceso en línea:http://hdl.handle.net/10115/2490
Access Level:acceso abierto
Palabra clave:Telecomunicaciones
3325 Tecnología de las Telecomunicaciones
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repository_id_str
spelling Robust Gamma-filter Using Support Vector MachinesCamps Valls, GustavoMartínez Ramón, ManelRojo-Álvarez, José LuisSoria Olivas, EmilioTelecomunicaciones3325 Tecnología de las TelecomunicacionesThis Letter presents a new approach to time-series modelling using the support vector machines (SVM). Although the g-filter can provide stability in several time-series models, the SVM is proposed here to provide robustness in the estimation of the g-filter coefficients. Examples in chaotic time-series prediction and channel equalization show the advantages of the joint SVM g-filter.Teoría de la Señal y Comunicaciones200920092009info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10115/2490reponame:BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlosinstname:Universidad Rey Juan CarlosInglésAtribución-NoComercial-SinDerivadas 3.0 Españahttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:burjcdigital.urjc.es:10115/24902026-06-24T12:48:17Z
dc.title.none.fl_str_mv Robust Gamma-filter Using Support Vector Machines
title Robust Gamma-filter Using Support Vector Machines
spellingShingle Robust Gamma-filter Using Support Vector Machines
Camps Valls, Gustavo
Telecomunicaciones
3325 Tecnología de las Telecomunicaciones
title_short Robust Gamma-filter Using Support Vector Machines
title_full Robust Gamma-filter Using Support Vector Machines
title_fullStr Robust Gamma-filter Using Support Vector Machines
title_full_unstemmed Robust Gamma-filter Using Support Vector Machines
title_sort Robust Gamma-filter Using Support Vector Machines
dc.creator.none.fl_str_mv Camps Valls, Gustavo
Martínez Ramón, Manel
Rojo-Álvarez, José Luis
Soria Olivas, Emilio
author Camps Valls, Gustavo
author_facet Camps Valls, Gustavo
Martínez Ramón, Manel
Rojo-Álvarez, José Luis
Soria Olivas, Emilio
author_role author
author2 Martínez Ramón, Manel
Rojo-Álvarez, José Luis
Soria Olivas, Emilio
author2_role author
author
author
dc.subject.none.fl_str_mv Telecomunicaciones
3325 Tecnología de las Telecomunicaciones
topic Telecomunicaciones
3325 Tecnología de las Telecomunicaciones
description This Letter presents a new approach to time-series modelling using the support vector machines (SVM). Although the g-filter can provide stability in several time-series models, the SVM is proposed here to provide robustness in the estimation of the g-filter coefficients. Examples in chaotic time-series prediction and channel equalization show the advantages of the joint SVM g-filter.
publishDate 2009
dc.date.none.fl_str_mv 2009
2009
2009
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10115/2490
url http://hdl.handle.net/10115/2490
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv Atribución-NoComercial-SinDerivadas 3.0 España
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial-SinDerivadas 3.0 España
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
instname:Universidad Rey Juan Carlos
instname_str Universidad Rey Juan Carlos
reponame_str BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
collection BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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