A two-gain NLMS algorithm for sparse system identification-Reference-Cited by-同舟云学术

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A two-gain NLMS algorithm for sparse system identification

Published:2022-11 Issue: Volume:200 Page:108636
ISSN:0165-1684
Container-title:Signal Processing
language:en
Short-container-title:Signal Processing

Author:

Luis Perez Fábio,André Pitz Ciro,Seara Rui^ORCID

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software,Control and Systems Engineering

Reference33 articles.

1. Adaptive Signal Processing;Widrow,1995

2. Adaptive Filter Theory;Haykin,2002

3. Exploiting sparsity in adaptive filters;Martin;IEEE Trans. Signal Process.,2002

4. Acoustic MIMO Signal Processing;Huang,2006

5. A unifying approach to the derivation of the class of PNLMS algorithms;Jelfs,2007

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1. Tracking Analysis of the $$\ell _0$$-LMS Algorithm;Circuits, Systems, and Signal Processing;2024-08-10

2. A Proportionate Maximum Total Complex Correntropy Algorithm for Sparse Systems;Circuits, Systems, and Signal Processing;2024-06-16

3. Robust augmented space recursive least-constrained-squares algorithms;Signal Processing;2024-06

4. A filter proportionate LMS algorithm based on the arctangent framework for sparse system identification;Signal, Image and Video Processing;2023-09-08

5. Sparse echo cancellation using variants of least mean fourth and least mean square algorithms;Facta universitatis - series: Electronics and Energetics;2023

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