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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2022
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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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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 |
work_keys_str_mv |
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