Identification of Wiener Models based on SVM and Orthonormal Bases

Autores
Gómez, Juan Carlos; Baeyens, Enrique
Año de publicación
2012
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In this paper, a novel method for the identification of the linear and nonlinear blocks in a Wiener model is presented. The method combines Support Vector Machines and Least Squares Prediction Error techniques. The identification is carried out by minimizing an augmented cost function defined as the sum of the standard structural risk function appearing in Support Vector Regression and the quadratic criterion on the prediction errors associated to Least Squares estimation methods. The properties of the proposed method are illustrated through simulation examples.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Wiener Models
Identification
SVM and Orthonormal Bases
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/123791

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network_name_str SEDICI (UNLP)
spelling Identification of Wiener Models based on SVM and Orthonormal BasesGómez, Juan CarlosBaeyens, EnriqueCiencias InformáticasWiener ModelsIdentificationSVM and Orthonormal BasesIn this paper, a novel method for the identification of the linear and nonlinear blocks in a Wiener model is presented. The method combines Support Vector Machines and Least Squares Prediction Error techniques. The identification is carried out by minimizing an augmented cost function defined as the sum of the standard structural risk function appearing in Support Vector Regression and the quadratic criterion on the prediction errors associated to Least Squares estimation methods. The properties of the proposed method are illustrated through simulation examples.Sociedad Argentina de Informática e Investigación Operativa2012-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf49-60http://sedici.unlp.edu.ar/handle/10915/123791enginfo:eu-repo/semantics/altIdentifier/url/https://41jaiio.sadio.org.ar/sites/default/files/5_AST_2012.pdfinfo:eu-repo/semantics/altIdentifier/issn/1850-2806info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:29:39Zoai:sedici.unlp.edu.ar:10915/123791Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:29:39.643SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Identification of Wiener Models based on SVM and Orthonormal Bases
title Identification of Wiener Models based on SVM and Orthonormal Bases
spellingShingle Identification of Wiener Models based on SVM and Orthonormal Bases
Gómez, Juan Carlos
Ciencias Informáticas
Wiener Models
Identification
SVM and Orthonormal Bases
title_short Identification of Wiener Models based on SVM and Orthonormal Bases
title_full Identification of Wiener Models based on SVM and Orthonormal Bases
title_fullStr Identification of Wiener Models based on SVM and Orthonormal Bases
title_full_unstemmed Identification of Wiener Models based on SVM and Orthonormal Bases
title_sort Identification of Wiener Models based on SVM and Orthonormal Bases
dc.creator.none.fl_str_mv Gómez, Juan Carlos
Baeyens, Enrique
author Gómez, Juan Carlos
author_facet Gómez, Juan Carlos
Baeyens, Enrique
author_role author
author2 Baeyens, Enrique
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Wiener Models
Identification
SVM and Orthonormal Bases
topic Ciencias Informáticas
Wiener Models
Identification
SVM and Orthonormal Bases
dc.description.none.fl_txt_mv In this paper, a novel method for the identification of the linear and nonlinear blocks in a Wiener model is presented. The method combines Support Vector Machines and Least Squares Prediction Error techniques. The identification is carried out by minimizing an augmented cost function defined as the sum of the standard structural risk function appearing in Support Vector Regression and the quadratic criterion on the prediction errors associated to Least Squares estimation methods. The properties of the proposed method are illustrated through simulation examples.
Sociedad Argentina de Informática e Investigación Operativa
description In this paper, a novel method for the identification of the linear and nonlinear blocks in a Wiener model is presented. The method combines Support Vector Machines and Least Squares Prediction Error techniques. The identification is carried out by minimizing an augmented cost function defined as the sum of the standard structural risk function appearing in Support Vector Regression and the quadratic criterion on the prediction errors associated to Least Squares estimation methods. The properties of the proposed method are illustrated through simulation examples.
publishDate 2012
dc.date.none.fl_str_mv 2012-08
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info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/123791
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dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/issn/1850-2806
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
49-60
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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