Design and Analysis of Robust Adaptive Filtering with the Hyperbolic Tangent Exponential Kernel M-Estimator Function for Active Noise Control

Iam Kim de S. Hermont, Andre R. Flores, Rodrigo C. de Lamare
8/18/2025
cs.LG

No confident code implementation found for this paper. 1 possible match can be shown below.

Abstract

In this work, we propose a robust adaptive filtering approach for active noise control applications in the presence of impulsive noise. In particular, we develop the filtered-x hyperbolic tangent exponential generalized Kernel M-estimate function (FXHEKM) robust adaptive algorithm. A statistical analysis of the proposed FXHEKM algorithm is carried out along with a study of its computational cost. {In order to evaluate the proposed FXHEKM algorithm, the mean-square error (MSE) and the average noise reduction (ANR) performance metrics have been adopted.} Numerical results show the efficiency of the proposed FXHEKM algorithm to cancel the presence of the additive spurious signals, such as \textbf{$α$}-stable noises against competing algorithms.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 1 weaker match is hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Cite this paper

@article{hermont2025design,
  title  = {Design and Analysis of Robust Adaptive Filtering with the Hyperbolic Tangent Exponential Kernel M-Estimator Function for Active Noise Control},
  author = {Iam Kim de S. Hermont and Andre R. Flores and Rodrigo C. de Lamare},
  year   = {2025},
  eprint = {2508.13018},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2508.13018v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2508.13018.svg)](https://codeofpaper.com/paper/2508.13018)

Discussion