Support Vector Robust Algorithms for Non-parametric Spectral Analysis

dc.contributor.author	Rojo-Álvarez, José Luis
dc.contributor.author	García Alberola, A
dc.contributor.author	Martínez Ramón, Manel
dc.contributor.author	Valdés, M
dc.contributor.author	Figueiras Vidal, Aníbal R
dc.contributor.author	Artés Rodríguez, A
dc.date.accessioned	2009-07-23T12:10:46Z
dc.date.available	2009-07-23T12:10:46Z
dc.date.issued	2009-07-23T12:10:46Z
dc.identifier.uri	http://hdl.handle.net/10115/2502
dc.description.abstract	A new approach to the non-parametric spectral estimation on the basis of the Support Vector (SV) framework is presented. Two algorithms are derived for both uniform and non-uniform sampling. The relationship between the SV free parameters and the underlying process statistics is discussed. The application in two real data examples, the sunspot numbers and the Heart Rate Variability, shows the higher resolution and robustness in SV spectral analysis algorithms	es
dc.language.iso	en	es
dc.subject	Telecomunicaciones	es
dc.title	Support Vector Robust Algorithms for Non-parametric Spectral Analysis	es
dc.type	info:eu-repo/semantics/conferenceObject	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess
dc.subject.unesco	3325 Tecnología de las Telecomunicaciones	es
dc.description.departamento	Teoría de la Señal y Comunicaciones