Adaptive filtering implemented over TMS320c6713 DSP platform for system identification

This paper presents the experimental development of software and hardware configuration to implement two adaptive algorithms: LMS (Least Mean Square) and RLS (Recursive Least Square), using TMS320C6713 DSP platform of Texas Instruments, for unknown systems identification. Methodology for implementat...

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Autores:
Jiménez-López, Fabián Rolando
Pardo-Beainy, Camilo Ernesto
Gutiérrez-Cáceres, Edgar Andrés
Tipo de recurso:
Fecha de publicación:
2014
Institución:
Universidad Santo Tomás
Repositorio:
Repositorio Institucional USTA
Idioma:
spa
OAI Identifier:
oai:repository.usta.edu.co:11634/36118
Acceso en línea:
http://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/726
http://hdl.handle.net/11634/36118
Palabra clave:
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Copyright (c) 2018 ITECKNE
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oai_identifier_str oai:repository.usta.edu.co:11634/36118
network_acronym_str SANTTOMAS2
network_name_str Repositorio Institucional USTA
repository_id_str
spelling Jiménez-López, Fabián RolandoPardo-Beainy, Camilo ErnestoGutiérrez-Cáceres, Edgar Andrés2021-09-24T13:17:27Z2021-09-24T13:17:27Z2014-12-31http://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/72610.15332/iteckne.v11i2.726http://hdl.handle.net/11634/36118This paper presents the experimental development of software and hardware configuration to implement two adaptive algorithms: LMS (Least Mean Square) and RLS (Recursive Least Square), using TMS320C6713 DSP platform of Texas Instruments, for unknown systems identification. Methodology for implementation and validation analysis for the adaptive algorithms is described in detail for real-time systems identification applications, and the experimental results were evaluated in terms of performance criterions in time domain, frequency domain, computational complexity, and accuracy.Este documento  describe  el  desarrollo  experimental  de  la  configuración  de  hardware  y software para implementar dos algoritmos adaptativos: el de Mínimos Cuadrados Promediados LMS (Least Mean Square) y  Mínimos  Cuadrados  Recursivos RLS (Recursive Least Square), usando la  plataforma  DSP  TMS320C713  de Texas   Instruments   para   identificación   de   sistemas  desconocidos. La metodología para la implementación y análisis de operación de los algoritmos adaptativos se presentan en detalle para aplicaciones de identificación de sistemas en tiempo real, y los resultados experimentales fueron evaluados en términos de criterios de desempeño en el dominio temporal, frecuencial, complejidad computacional y precisión.application/pdfspaUniversidad Santo Tomás. Seccional Bucaramangahttp://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/726/572ITECKNE; Vol 11 No 2 (2014); 157-171ITECKNE; Vol 11 No 2 (2014); 157-1712339-34831692-1798Copyright (c) 2018 ITECKNEhttp://purl.org/coar/access_right/c_abf2Adaptive filtering implemented over TMS320c6713 DSP platform for system identificationFiltrado adaptativo implementado sobre plataforma DSP TMS320c6713 para identificación de sistemasinfo:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb111634/36118oai:repository.usta.edu.co:11634/361182023-07-14 16:20:35.887metadata only accessRepositorio Universidad Santo Tomásnoreply@usta.edu.co
dc.title.spa.fl_str_mv Adaptive filtering implemented over TMS320c6713 DSP platform for system identification
dc.title.alternative.eng.fl_str_mv Filtrado adaptativo implementado sobre plataforma DSP TMS320c6713 para identificación de sistemas
title Adaptive filtering implemented over TMS320c6713 DSP platform for system identification
spellingShingle Adaptive filtering implemented over TMS320c6713 DSP platform for system identification
title_short Adaptive filtering implemented over TMS320c6713 DSP platform for system identification
title_full Adaptive filtering implemented over TMS320c6713 DSP platform for system identification
title_fullStr Adaptive filtering implemented over TMS320c6713 DSP platform for system identification
title_full_unstemmed Adaptive filtering implemented over TMS320c6713 DSP platform for system identification
title_sort Adaptive filtering implemented over TMS320c6713 DSP platform for system identification
dc.creator.fl_str_mv Jiménez-López, Fabián Rolando
Pardo-Beainy, Camilo Ernesto
Gutiérrez-Cáceres, Edgar Andrés
dc.contributor.author.none.fl_str_mv Jiménez-López, Fabián Rolando
Pardo-Beainy, Camilo Ernesto
Gutiérrez-Cáceres, Edgar Andrés
description This paper presents the experimental development of software and hardware configuration to implement two adaptive algorithms: LMS (Least Mean Square) and RLS (Recursive Least Square), using TMS320C6713 DSP platform of Texas Instruments, for unknown systems identification. Methodology for implementation and validation analysis for the adaptive algorithms is described in detail for real-time systems identification applications, and the experimental results were evaluated in terms of performance criterions in time domain, frequency domain, computational complexity, and accuracy.
publishDate 2014
dc.date.issued.none.fl_str_mv 2014-12-31
dc.date.accessioned.none.fl_str_mv 2021-09-24T13:17:27Z
dc.date.available.none.fl_str_mv 2021-09-24T13:17:27Z
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.drive.none.fl_str_mv info:eu-repo/semantics/article
dc.identifier.none.fl_str_mv http://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/726
10.15332/iteckne.v11i2.726
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/11634/36118
url http://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/726
http://hdl.handle.net/11634/36118
identifier_str_mv 10.15332/iteckne.v11i2.726
dc.language.iso.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv http://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/726/572
dc.relation.citationissue.spa.fl_str_mv ITECKNE; Vol 11 No 2 (2014); 157-171
dc.relation.citationissue.eng.fl_str_mv ITECKNE; Vol 11 No 2 (2014); 157-171
dc.relation.citationissue.none.fl_str_mv 2339-3483
1692-1798
dc.rights.eng.fl_str_mv Copyright (c) 2018 ITECKNE
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv Copyright (c) 2018 ITECKNE
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.eng.fl_str_mv Universidad Santo Tomás. Seccional Bucaramanga
institution Universidad Santo Tomás
repository.name.fl_str_mv Repositorio Universidad Santo Tomás
repository.mail.fl_str_mv noreply@usta.edu.co
_version_ 1782026386121162752

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