Robust Gamma-filter Using Support Vector Machines

dc.contributor.authorCamps Valls, Gustavo
dc.contributor.authorMartínez Ramón, Manel
dc.contributor.authorRojo-Álvarez, José Luis
dc.contributor.authorSoria Olivas, Emilio
dc.date.accessioned2009-07-23T09:19:34Z
dc.date.available2009-07-23T09:19:34Z
dc.date.issued2009-07-23T09:19:34Z
dc.description.abstractThis 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.departamentoTeoría de la Señal y Comunicaciones
dc.identifier.doi10.1016/j.neucom.2004.07.003es
dc.identifier.issn0925-2312
dc.identifier.urihttp://hdl.handle.net/10115/2490
dc.language.isoenes
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectTelecomunicacioneses
dc.subject.unesco3325 Tecnología de las Telecomunicacioneses
dc.titleRobust Gamma-filter Using Support Vector Machineses
dc.typeinfo:eu-repo/semantics/articlees

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