Selection of the convergence step of the Fx-LMS algorithm

[EN] The choice of a suitable convergence step that allows the fast convergence of the filtered-x LMS algorithm in practical scenarios is usually carried out by trial and error, since the theoretical developments provide only indicative values. The particularity of the filtered-x structure, which ad...

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Autores: Ferrer Contreras, Miguel|||0000-0002-8743-1887, de Diego Antón, María|||0000-0001-9948-3396, García Mollá, Víctor Manuel|||0000-0003-4768-7367, Gonzalez, Alberto|||0000-0002-6984-3212
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/204938
Acceso en línea:https://riunet.upv.es/handle/10251/204938
Access Level:acceso abierto
Palabra clave:Adaptive filtering
Filtered-x LMS
Active noise control
Convergence analysis
TEORÍA DE LA SEÑAL Y COMUNICACIONES
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades
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spelling Selection of the convergence step of the Fx-LMS algorithmFerrer Contreras, Miguel|||0000-0002-8743-1887de Diego Antón, María|||0000-0001-9948-3396García Mollá, Víctor Manuel|||0000-0003-4768-7367Gonzalez, Alberto|||0000-0002-6984-3212Adaptive filteringFiltered-x LMSActive noise controlConvergence analysisTEORÍA DE LA SEÑAL Y COMUNICACIONESCIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades[EN] The choice of a suitable convergence step that allows the fast convergence of the filtered-x LMS algorithm in practical scenarios is usually carried out by trial and error, since the theoretical developments provide only indicative values. The particularity of the filtered-x structure, which adds a delay between the output of the adaptive filter and the error signal and colors the reference signal, increases the inaccuracy of the theoretical models. Furthermore, the use of band-limited reference signals is beyond the scope of most theoretical studies, which focus on the cases of full-band reference signals, making it difficult to extrapolate these models to band-limited signals. In this paper, we propose a low-cost and meaningful method for selecting the convergence step that is well tuned in most practical cases. It can be used regardless of the type of the reference signal, the system delays, and the nature of the filter required in the filtered-x structure. Numerical simulations are performed to validate the effectiveness of the proposed approach.This work has been partially supported by RTI2018-098085-BC41 and PID2021-125736OB-I00 (MCIN/AEI/10.13039/501100011033/, "ERDF A way of making Europe") and GVA through PROMETEO/2019/109.ElsevierEscuela Técnica Superior de Ingeniería de TelecomunicaciónDepartamento de Sistemas Informáticos y ComputaciónDepartamento de ComunicacionesInstituto Universitario de Telecomunicación y Aplicaciones MultimediaEscuela Técnica Superior de Ingeniería InformáticaGENERALITAT VALENCIANAAGENCIA ESTATAL DE INVESTIGACIONEuropean Regional Development FundUniversitat Politècnica de ValènciaRepositorio Institucional de la Universitat Politècnica de València Riunet20232023-10-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/204938reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 PID2021-125736OB-I00 ADAPTIVE SOUND-PROCESSING TECHNOLOGIES FOR SOUNDFIELD DEPLOYMENT: ALGORITHMS, TOOLS AND TEST BEDSGeneralitat Valenciana https://doi.org/10.13039/501100003359 PROMETEO%2F2019%2F109 COMUNICACION Y COMPUTACION INTELIGENTES Y SOCIALESAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 RTI2018-098085-B-C41-AR DYNAMIC ACOUSTIC NETWORKS FOR CHANGING ENVIROMENTSGeneralitat Valenciana https://doi.org/10.13039/501100003359 CIPROM%2F2022%2F20 COMPUTACION Y TRATAMIENTO DE LA SEÑAL PARA LA SOCIEDAD Y LA INDUSTRIA DIGITALESopen accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/2049382026-06-13T07:49:27Z
dc.title.none.fl_str_mv Selection of the convergence step of the Fx-LMS algorithm
title Selection of the convergence step of the Fx-LMS algorithm
spellingShingle Selection of the convergence step of the Fx-LMS algorithm
Ferrer Contreras, Miguel|||0000-0002-8743-1887
Adaptive filtering
Filtered-x LMS
Active noise control
Convergence analysis
TEORÍA DE LA SEÑAL Y COMUNICACIONES
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades
title_short Selection of the convergence step of the Fx-LMS algorithm
title_full Selection of the convergence step of the Fx-LMS algorithm
title_fullStr Selection of the convergence step of the Fx-LMS algorithm
title_full_unstemmed Selection of the convergence step of the Fx-LMS algorithm
title_sort Selection of the convergence step of the Fx-LMS algorithm
dc.creator.none.fl_str_mv Ferrer Contreras, Miguel|||0000-0002-8743-1887
de Diego Antón, María|||0000-0001-9948-3396
García Mollá, Víctor Manuel|||0000-0003-4768-7367
Gonzalez, Alberto|||0000-0002-6984-3212
author Ferrer Contreras, Miguel|||0000-0002-8743-1887
author_facet Ferrer Contreras, Miguel|||0000-0002-8743-1887
de Diego Antón, María|||0000-0001-9948-3396
García Mollá, Víctor Manuel|||0000-0003-4768-7367
Gonzalez, Alberto|||0000-0002-6984-3212
author_role author
author2 de Diego Antón, María|||0000-0001-9948-3396
García Mollá, Víctor Manuel|||0000-0003-4768-7367
Gonzalez, Alberto|||0000-0002-6984-3212
author2_role author
author
author
dc.contributor.none.fl_str_mv Escuela Técnica Superior de Ingeniería de Telecomunicación
Departamento de Sistemas Informáticos y Computación
Departamento de Comunicaciones
Instituto Universitario de Telecomunicación y Aplicaciones Multimedia
Escuela Técnica Superior de Ingeniería Informática
GENERALITAT VALENCIANA
AGENCIA ESTATAL DE INVESTIGACION
European Regional Development Fund
Universitat Politècnica de València
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Adaptive filtering
Filtered-x LMS
Active noise control
Convergence analysis
TEORÍA DE LA SEÑAL Y COMUNICACIONES
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades
topic Adaptive filtering
Filtered-x LMS
Active noise control
Convergence analysis
TEORÍA DE LA SEÑAL Y COMUNICACIONES
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades
description [EN] The choice of a suitable convergence step that allows the fast convergence of the filtered-x LMS algorithm in practical scenarios is usually carried out by trial and error, since the theoretical developments provide only indicative values. The particularity of the filtered-x structure, which adds a delay between the output of the adaptive filter and the error signal and colors the reference signal, increases the inaccuracy of the theoretical models. Furthermore, the use of band-limited reference signals is beyond the scope of most theoretical studies, which focus on the cases of full-band reference signals, making it difficult to extrapolate these models to band-limited signals. In this paper, we propose a low-cost and meaningful method for selecting the convergence step that is well tuned in most practical cases. It can be used regardless of the type of the reference signal, the system delays, and the nature of the filter required in the filtered-x structure. Numerical simulations are performed to validate the effectiveness of the proposed approach.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-10-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/204938
url https://riunet.upv.es/handle/10251/204938
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 PID2021-125736OB-I00 ADAPTIVE SOUND-PROCESSING TECHNOLOGIES FOR SOUNDFIELD DEPLOYMENT: ALGORITHMS, TOOLS AND TEST BEDS
Generalitat Valenciana https://doi.org/10.13039/501100003359 PROMETEO%2F2019%2F109 COMUNICACION Y COMPUTACION INTELIGENTES Y SOCIALES
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 RTI2018-098085-B-C41-AR DYNAMIC ACOUSTIC NETWORKS FOR CHANGING ENVIROMENTS
Generalitat Valenciana https://doi.org/10.13039/501100003359 CIPROM%2F2022%2F20 COMPUTACION Y TRATAMIENTO DE LA SEÑAL PARA LA SOCIEDAD Y LA INDUSTRIA DIGITALES
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301629

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