Application of Affine Estimators to Single Tone Frequency Estimation

Autores
Gama, Fernando; Casaglia, Daniel; Cernuschi-Frías, Bruno
Año de publicación
2012
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Affine estimation has emerged as a promising technique to reduce the mean squared error (MSE) between the estimated parameters and the true value of these parameters. The aim of this paper is to obtain an affine estimator for the frequency of a complex sinusoid corrupted by white gaussian noise. Additionally, an adaptive technique is presented. The simulation results clearly show that affine estimators have better performance than unbiased estimators such as the maximum likelihood estimator (MLE) and the Fu-Kam approximation.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Single Tone Estimation
Affine Estimators
Mean Squared Error
Adaptive Algorithm
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:10915/123804

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spelling Application of Affine Estimators to Single Tone Frequency EstimationGama, FernandoCasaglia, DanielCernuschi-Frías, BrunoCiencias InformáticasSingle Tone EstimationAffine EstimatorsMean Squared ErrorAdaptive AlgorithmAffine estimation has emerged as a promising technique to reduce the mean squared error (MSE) between the estimated parameters and the true value of these parameters. The aim of this paper is to obtain an affine estimator for the frequency of a complex sinusoid corrupted by white gaussian noise. Additionally, an adaptive technique is presented. The simulation results clearly show that affine estimators have better performance than unbiased estimators such as the maximum likelihood estimator (MLE) and the Fu-Kam approximation.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/pdf121-131http://sedici.unlp.edu.ar/handle/10915/123804enginfo:eu-repo/semantics/altIdentifier/url/https://41jaiio.sadio.org.ar/sites/default/files/11_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:10915/123804Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:29:39.662SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Application of Affine Estimators to Single Tone Frequency Estimation
title Application of Affine Estimators to Single Tone Frequency Estimation
spellingShingle Application of Affine Estimators to Single Tone Frequency Estimation
Gama, Fernando
Ciencias Informáticas
Single Tone Estimation
Affine Estimators
Mean Squared Error
Adaptive Algorithm
title_short Application of Affine Estimators to Single Tone Frequency Estimation
title_full Application of Affine Estimators to Single Tone Frequency Estimation
title_fullStr Application of Affine Estimators to Single Tone Frequency Estimation
title_full_unstemmed Application of Affine Estimators to Single Tone Frequency Estimation
title_sort Application of Affine Estimators to Single Tone Frequency Estimation
dc.creator.none.fl_str_mv Gama, Fernando
Casaglia, Daniel
Cernuschi-Frías, Bruno
author Gama, Fernando
author_facet Gama, Fernando
Casaglia, Daniel
Cernuschi-Frías, Bruno
author_role author
author2 Casaglia, Daniel
Cernuschi-Frías, Bruno
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Single Tone Estimation
Affine Estimators
Mean Squared Error
Adaptive Algorithm
topic Ciencias Informáticas
Single Tone Estimation
Affine Estimators
Mean Squared Error
Adaptive Algorithm
dc.description.none.fl_txt_mv Affine estimation has emerged as a promising technique to reduce the mean squared error (MSE) between the estimated parameters and the true value of these parameters. The aim of this paper is to obtain an affine estimator for the frequency of a complex sinusoid corrupted by white gaussian noise. Additionally, an adaptive technique is presented. The simulation results clearly show that affine estimators have better performance than unbiased estimators such as the maximum likelihood estimator (MLE) and the Fu-Kam approximation.
Sociedad Argentina de Informática e Investigación Operativa
description Affine estimation has emerged as a promising technique to reduce the mean squared error (MSE) between the estimated parameters and the true value of these parameters. The aim of this paper is to obtain an affine estimator for the frequency of a complex sinusoid corrupted by white gaussian noise. Additionally, an adaptive technique is presented. The simulation results clearly show that affine estimators have better performance than unbiased estimators such as the maximum likelihood estimator (MLE) and the Fu-Kam approximation.
publishDate 2012
dc.date.none.fl_str_mv 2012-08
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info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
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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
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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
121-131
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