An adaptive algorithm, based on modified tanh non-linearity and fractional processing, for impulsive active noise control systems

Research output: Contribution to journalArticle

Abstract

This paper presents an adaptive algorithm for active control of noise sources that are of impulsive nature. The impulsive type sources can be better modeled as a stable distribution than the Gaussian. However, for stable distributions, the variance (second order moment) is infinite. The standard adaptive filtering algorithms, which are based on minimizing variance and assuming Gaussian distribution, converge slowly or become even unstable for stable (impulsive) processes. In order to improve the performance of the standard filtered-x least mean square (FxLMS)-based impulsive active noise control (IANC) systems, we propose two enhancements in this paper. First, we propose employing modified tanh function-based nonlinear process in the reference and error paths of the standard FxLMS algorithm. The main idea is to automatically give an appropriate weight to the various samples in the process, i.e. appropriately threshold the very large values so that system remains stable, and give more weight to samples below threshold limit so that the convergence speed can be improved. A second proposal is to incorporate the fractional-gradient computation in the update vector of IANC adaptive filter. Computer simulations have been carried out using experimental data for the acoustic paths. The simulation results demonstrate that the proposed algorithm is very effective for IANC systems.

Original languageEnglish
Pages (from-to)495-508
Number of pages14
JournalJournal of Low Frequency Noise Vibration and Active Control
Volume37
Issue number3
DOIs
Publication statusPublished - Sep 1 2018

Fingerprint

Active noise control
Adaptive algorithms
nonlinearity
control system
Control systems
Processing
Adaptive filtering
Gaussian distribution
Adaptive filters
active control
adaptive filters
thresholds
Acoustics
normal density functions
computer simulation
proposals
acoustics
computerized simulation
Computer simulation
filter

Keywords

  • fractional signal processing
  • FxLMS algorithm
  • Impulsive noise control
  • stable distributions

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Acoustics and Ultrasonics
  • Mechanics of Materials
  • Geophysics
  • Mechanical Engineering

Cite this

@article{68422621c34a4098879e5a693ef5eb22,
title = "An adaptive algorithm, based on modified tanh non-linearity and fractional processing, for impulsive active noise control systems",
abstract = "This paper presents an adaptive algorithm for active control of noise sources that are of impulsive nature. The impulsive type sources can be better modeled as a stable distribution than the Gaussian. However, for stable distributions, the variance (second order moment) is infinite. The standard adaptive filtering algorithms, which are based on minimizing variance and assuming Gaussian distribution, converge slowly or become even unstable for stable (impulsive) processes. In order to improve the performance of the standard filtered-x least mean square (FxLMS)-based impulsive active noise control (IANC) systems, we propose two enhancements in this paper. First, we propose employing modified tanh function-based nonlinear process in the reference and error paths of the standard FxLMS algorithm. The main idea is to automatically give an appropriate weight to the various samples in the process, i.e. appropriately threshold the very large values so that system remains stable, and give more weight to samples below threshold limit so that the convergence speed can be improved. A second proposal is to incorporate the fractional-gradient computation in the update vector of IANC adaptive filter. Computer simulations have been carried out using experimental data for the acoustic paths. The simulation results demonstrate that the proposed algorithm is very effective for IANC systems.",
keywords = "fractional signal processing, FxLMS algorithm, Impulsive noise control, stable distributions",
author = "Akhtar, {Muhammad T.}",
year = "2018",
month = "9",
day = "1",
doi = "10.1177/1461348417725952",
language = "English",
volume = "37",
pages = "495--508",
journal = "Journal of Low Frequency Noise Vibration and Active Control",
issn = "1461-3484",
publisher = "Multi-Science Publishing Co. Ltd",
number = "3",

}

TY - JOUR

T1 - An adaptive algorithm, based on modified tanh non-linearity and fractional processing, for impulsive active noise control systems

AU - Akhtar, Muhammad T.

PY - 2018/9/1

Y1 - 2018/9/1

N2 - This paper presents an adaptive algorithm for active control of noise sources that are of impulsive nature. The impulsive type sources can be better modeled as a stable distribution than the Gaussian. However, for stable distributions, the variance (second order moment) is infinite. The standard adaptive filtering algorithms, which are based on minimizing variance and assuming Gaussian distribution, converge slowly or become even unstable for stable (impulsive) processes. In order to improve the performance of the standard filtered-x least mean square (FxLMS)-based impulsive active noise control (IANC) systems, we propose two enhancements in this paper. First, we propose employing modified tanh function-based nonlinear process in the reference and error paths of the standard FxLMS algorithm. The main idea is to automatically give an appropriate weight to the various samples in the process, i.e. appropriately threshold the very large values so that system remains stable, and give more weight to samples below threshold limit so that the convergence speed can be improved. A second proposal is to incorporate the fractional-gradient computation in the update vector of IANC adaptive filter. Computer simulations have been carried out using experimental data for the acoustic paths. The simulation results demonstrate that the proposed algorithm is very effective for IANC systems.

AB - This paper presents an adaptive algorithm for active control of noise sources that are of impulsive nature. The impulsive type sources can be better modeled as a stable distribution than the Gaussian. However, for stable distributions, the variance (second order moment) is infinite. The standard adaptive filtering algorithms, which are based on minimizing variance and assuming Gaussian distribution, converge slowly or become even unstable for stable (impulsive) processes. In order to improve the performance of the standard filtered-x least mean square (FxLMS)-based impulsive active noise control (IANC) systems, we propose two enhancements in this paper. First, we propose employing modified tanh function-based nonlinear process in the reference and error paths of the standard FxLMS algorithm. The main idea is to automatically give an appropriate weight to the various samples in the process, i.e. appropriately threshold the very large values so that system remains stable, and give more weight to samples below threshold limit so that the convergence speed can be improved. A second proposal is to incorporate the fractional-gradient computation in the update vector of IANC adaptive filter. Computer simulations have been carried out using experimental data for the acoustic paths. The simulation results demonstrate that the proposed algorithm is very effective for IANC systems.

KW - fractional signal processing

KW - FxLMS algorithm

KW - Impulsive noise control

KW - stable distributions

UR - http://www.scopus.com/inward/record.url?scp=85053698289&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85053698289&partnerID=8YFLogxK

U2 - 10.1177/1461348417725952

DO - 10.1177/1461348417725952

M3 - Article

AN - SCOPUS:85053698289

VL - 37

SP - 495

EP - 508

JO - Journal of Low Frequency Noise Vibration and Active Control

JF - Journal of Low Frequency Noise Vibration and Active Control

SN - 1461-3484

IS - 3

ER -