Robust Gamma-filter Using Support Vector Machines

dc.contributor.author	Camps Valls, Gustavo
dc.contributor.author	Martínez Ramón, Manel
dc.contributor.author	Rojo-Álvarez, José Luis
dc.contributor.author	Soria Olivas, Emilio
dc.date.accessioned	2009-07-23T09:19:34Z
dc.date.available	2009-07-23T09:19:34Z
dc.date.issued	2009-07-23T09:19:34Z
dc.description.abstract	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.	es
dc.description.departamento	Teoría de la Señal y Comunicaciones
dc.identifier.doi	10.1016/j.neucom.2004.07.003	es
dc.identifier.issn	0925-2312
dc.identifier.uri	http://hdl.handle.net/10115/2490
dc.language.iso	en	es
dc.rights	Atribución-NoComercial-SinDerivadas 3.0 España	*
dc.rights.accessRights	info:eu-repo/semantics/openAccess	es
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/	*
dc.subject	Telecomunicaciones	es
dc.subject.unesco	3325 Tecnología de las Telecomunicaciones	es
dc.title	Robust Gamma-filter Using Support Vector Machines	es
dc.type	info:eu-repo/semantics/article	es

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