JOURNAL ARTICLE

Sparsity-inducing modified filtered-x affine projection algorithms for active noise control

Abstract

This paper describes a novel technique for promoting sparsity in the modified filtered-x algorithms required for active noise control. The proposed algorithms are based on recent techniques incorporating approximations to the l 0 -norm in the cost functions that are used to derive adaptive filtering algorithms. In particular, zero-attracting and reweighted zero-attracting filtered-x adaptive algorithms are developed and considered for active noise control problems. The results of simulations indicate that the proposed techniques improve the convergence of the existing modified algorithm in the case where the primary and secondary paths exhibit a degree of sparsity.

Keywords:
Algorithm Active noise control Noise (video) Convergence (economics) Computer science Adaptive filter Norm (philosophy) Projection (relational algebra) Affine transformation Mathematics Artificial intelligence Noise reduction

Metrics

3
Cited By
0.32
FWCI (Field Weighted Citation Impact)
21
Refs
0.58
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Adaptive Filtering Techniques
Physical Sciences →  Engineering →  Computational Mechanics
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Blind Source Separation Techniques
Physical Sciences →  Computer Science →  Signal Processing

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