New variant of NLMS/F algorithm with low computational cost

Adaptive filters are used in a wide variety of signal processing applications (e.g., acoustic echo cancellation, system identification, channel equalization, etc.). Adaptive algorithms are an essential part of adaptive filters since they update the filter coefficients to model the desired response....

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Autores principales: Hidalgo Hernández, Laura Jazmín, Vázquez Piña, Ángel Alfonso, Maya Rosales, Xochitl, Avalos Ochoa, Juan Gerardo, Sánchez Rivera, Giovanny
Formato: Artículo publishedVersion
Lenguaje:Español
Publicado: FIUBA 2022
Materias:
NLMF algorithm; NLMS/F algorithm; set membership; adaptive filtering
Algoritmo NLMF; algoritmo NLMS/F; conjunto de membresías; filtrado adaptativo.
Acceso en línea:http://elektron.fi.uba.ar/index.php/elektron/article/view/163
http://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=elektron&d=163_oai
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Repositorio Digital de la Universidad de Buenos Aires (UBA) de Universidad de Buenos Aires
id I28-R145-163_oai
record_format dspace
spelling I28-R145-163_oai2023-08-08 Hidalgo Hernández, Laura Jazmín Vázquez Piña, Ángel Alfonso Maya Rosales, Xochitl Avalos Ochoa, Juan Gerardo Sánchez Rivera, Giovanny 2022-12-15 Adaptive filters are used in a wide variety of signal processing applications (e.g., acoustic echo cancellation, system identification, channel equalization, etc.). Adaptive algorithms are an essential part of adaptive filters since they update the filter coefficients to model the desired response. Therefore, adaptive algorithms must have low computational cost and high speed of convergence. In this paper, a new variant of the Normalized Least-Mean-Fourth (NLMF) algorithm based on set membership is presented, in addition, a method to automatically adjust the step size is presented. To evaluate its performance, the algorithm was simulated in system identification and acoustic echo cancellation applications. The results demonstrate that the proposed algorithm improves the convergence speed and exhibits low computational cost compared to the conventional NLMS/F algorithm. El filtrado adaptativo es utilizado ampliamente en aplicaciones de procesamiento de señales, entre las que se encuentran: cancelación de eco acústico, identificación de sistemas, ecualización de canales, entre otras. El elemento más importante de un filtro adaptativo es el algoritmo adaptativo, el cual tiene la función de ajustar los coeficientes del filtro para minimizar la señal de error. Por tal motivo, es necesario un algoritmo adaptativo que presente una baja carga computacional y una alta velocidad de convergencia. En este artículo, se presenta una nueva variante del algoritmo de mínimos promediados de cuarto orden normalizado (NLMF - Normalized Least-Mean-Fourth) basado en el conjunto de membresías, además, se propone un método que permite ajustar el factor de convergencia de forma automática. Para evaluar su funcionamiento, el algoritmo se simuló en un identificador de sistemas y un cancelador de eco acústico. Los resultados obtenidos demuestran que el algoritmo propuesto mejora la velocidad de convergencia, además de exhibir un bajo costo computacional en comparación con el algoritmo NLMS/F convencional. application/pdf text/html http://elektron.fi.uba.ar/index.php/elektron/article/view/163 10.37537/rev.elektron.6.2.163.2022 spa FIUBA http://elektron.fi.uba.ar/index.php/elektron/article/view/163/300 http://elektron.fi.uba.ar/index.php/elektron/article/view/163/312 http://elektron.fi.uba.ar/index.php/elektron/article/downloadSuppFile/163/205 http://elektron.fi.uba.ar/index.php/elektron/article/downloadSuppFile/163/223 Copyright (c) 2022 Laura Jazmín Hidalgo Hernández, Ángel Alfonso Vázquez Piña, Xochitl Maya Rosales, Juan Gerardo Avalos Ochoa, Giovanny Sánchez Rivera http://creativecommons.org/licenses/by-nc-nd/4.0 Elektron; Vol 6, No 2 (2022); 96-100 Elektron; Vol 6, No 2 (2022); 96-100 2525-0159 NLMF algorithm; NLMS/F algorithm; set membership; adaptive filtering Algoritmo NLMF; algoritmo NLMS/F; conjunto de membresías; filtrado adaptativo. New variant of NLMS/F algorithm with low computational cost Nueva variante del algoritmo NLMS/F de bajo costo computacional info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=elektron&d=163_oai
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-145
collection Repositorio Digital de la Universidad de Buenos Aires (UBA)
language Español
orig_language_str_mv spa
topic NLMF algorithm; NLMS/F algorithm; set membership; adaptive filtering
Algoritmo NLMF; algoritmo NLMS/F; conjunto de membresías; filtrado adaptativo.
spellingShingle NLMF algorithm; NLMS/F algorithm; set membership; adaptive filtering
Algoritmo NLMF; algoritmo NLMS/F; conjunto de membresías; filtrado adaptativo.
Hidalgo Hernández, Laura Jazmín
Vázquez Piña, Ángel Alfonso
Maya Rosales, Xochitl
Avalos Ochoa, Juan Gerardo
Sánchez Rivera, Giovanny
New variant of NLMS/F algorithm with low computational cost
topic_facet NLMF algorithm; NLMS/F algorithm; set membership; adaptive filtering
Algoritmo NLMF; algoritmo NLMS/F; conjunto de membresías; filtrado adaptativo.
description Adaptive filters are used in a wide variety of signal processing applications (e.g., acoustic echo cancellation, system identification, channel equalization, etc.). Adaptive algorithms are an essential part of adaptive filters since they update the filter coefficients to model the desired response. Therefore, adaptive algorithms must have low computational cost and high speed of convergence. In this paper, a new variant of the Normalized Least-Mean-Fourth (NLMF) algorithm based on set membership is presented, in addition, a method to automatically adjust the step size is presented. To evaluate its performance, the algorithm was simulated in system identification and acoustic echo cancellation applications. The results demonstrate that the proposed algorithm improves the convergence speed and exhibits low computational cost compared to the conventional NLMS/F algorithm.
format Artículo
publishedVersion
author Hidalgo Hernández, Laura Jazmín
Vázquez Piña, Ángel Alfonso
Maya Rosales, Xochitl
Avalos Ochoa, Juan Gerardo
Sánchez Rivera, Giovanny
author_facet Hidalgo Hernández, Laura Jazmín
Vázquez Piña, Ángel Alfonso
Maya Rosales, Xochitl
Avalos Ochoa, Juan Gerardo
Sánchez Rivera, Giovanny
author_sort Hidalgo Hernández, Laura Jazmín
title New variant of NLMS/F algorithm with low computational cost
title_short New variant of NLMS/F algorithm with low computational cost
title_full New variant of NLMS/F algorithm with low computational cost
title_fullStr New variant of NLMS/F algorithm with low computational cost
title_full_unstemmed New variant of NLMS/F algorithm with low computational cost
title_sort new variant of nlms/f algorithm with low computational cost
publisher FIUBA
publishDate 2022
url http://elektron.fi.uba.ar/index.php/elektron/article/view/163
http://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=elektron&d=163_oai
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