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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/123791
Ver los metadatos del registro completo
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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 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia 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 |
url |
http://sedici.unlp.edu.ar/handle/10915/123791 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
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dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf 49-60 |
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