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Autor principal: Wang, Boxiang
Formato: Preprint
Publicado: 2024
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Acceso en línea:https://arxiv.org/abs/2402.09449
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author Wang, Boxiang
author_facet Wang, Boxiang
contents Multichannel filtered reference least mean square (McFxLMS) algorithms are widely utilized in adaptive multichannel active noise control (MCANC) applications. As a critical and high-computationally efficient adaptive critical algorithm, it also typically works as a benchmark for comparative studies of the new algorithms proposed by peers and researchers. However, up to now, there are few open-source codes for the FxLMS algorithm, especially for large-count channels. Therefore, this work provides a MATLAB code for the McFxLMS algorithm, which can be used for the arbitrary number of channels system. The code is available on GitHub and Mathworks.
format Preprint
id arxiv_https___arxiv_org_abs_2402_09449
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Implementation of the Multichannel Filtered Reference Least Mean Square (McFxLMS) Algorithm with an Arbitrary Number of Channels by Using MATLAB
Wang, Boxiang
Signal Processing
Multichannel filtered reference least mean square (McFxLMS) algorithms are widely utilized in adaptive multichannel active noise control (MCANC) applications. As a critical and high-computationally efficient adaptive critical algorithm, it also typically works as a benchmark for comparative studies of the new algorithms proposed by peers and researchers. However, up to now, there are few open-source codes for the FxLMS algorithm, especially for large-count channels. Therefore, this work provides a MATLAB code for the McFxLMS algorithm, which can be used for the arbitrary number of channels system. The code is available on GitHub and Mathworks.
title Implementation of the Multichannel Filtered Reference Least Mean Square (McFxLMS) Algorithm with an Arbitrary Number of Channels by Using MATLAB
topic Signal Processing
url https://arxiv.org/abs/2402.09449