Fractional processing-based active noise control algorithm for impulsive noise

Muhammad Tahir Akhtar, Muhammad Asifzahoor Raja

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper deals with active noise control (ANC) for impulsive noise sources for which the filtered-x least mean square (FxLMS) algorithm becomes unstable. By minimizing the fractional lower order moment, the resulting filtered-x least mean p-power (FxLMP) algorithm has an update vector being computed using sign operator and fractional power of the residual error signal. This results in improved robustness as compared with the FxLMS algorithm; however, the convergence speed is very slow. Improvement in convergence speed can be achieved by computing a fractional power for the error as well as for the (filtered) reference signal, combined with efficient normalization of the step-size parameter. This results in filtered-x modified generalized normalized Least mean p-power (FxMGNLMP) algorithm. In this paper we develop a new fractional processing-based adaptive algorithm for ANC of impulsive noise sources. The main idea is to compute a modified update vector for FxMGNLMP algorithm by computing fractional power of the tap-weight vector, and add this update term (after including an appropriate scaling factor) to the original update equation of the FxMGNLMP algorithm. The results of computer simulations demonstrate improved performance of the proposed approach especially when the noise source is highly impulsive.

Original languageEnglish
Title of host publication2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages10-14
Number of pages5
ISBN (Electronic)9781479919482
DOIs
Publication statusPublished - Aug 31 2015
EventIEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Chengdu, China
Duration: Jul 12 2015Jul 15 2015

Conference

ConferenceIEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015
CountryChina
CityChengdu
Period7/12/157/15/15

Fingerprint

Active noise control
Impulse noise
Processing
Adaptive algorithms
Computer simulation

Keywords

  • Active noise control
  • fractional LMS
  • fractional lower order moment (FLOM)
  • generalized LMP algorithm
  • non-Gaussian stable processes

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

Cite this

Akhtar, M. T., & Raja, M. A. (2015). Fractional processing-based active noise control algorithm for impulsive noise. In 2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings (pp. 10-14). [7230352] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ChinaSIP.2015.7230352

Fractional processing-based active noise control algorithm for impulsive noise. / Akhtar, Muhammad Tahir; Raja, Muhammad Asifzahoor.

2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. p. 10-14 7230352.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Akhtar, MT & Raja, MA 2015, Fractional processing-based active noise control algorithm for impulsive noise. in 2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings., 7230352, Institute of Electrical and Electronics Engineers Inc., pp. 10-14, IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015, Chengdu, China, 7/12/15. https://doi.org/10.1109/ChinaSIP.2015.7230352
Akhtar MT, Raja MA. Fractional processing-based active noise control algorithm for impulsive noise. In 2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2015. p. 10-14. 7230352 https://doi.org/10.1109/ChinaSIP.2015.7230352
Akhtar, Muhammad Tahir ; Raja, Muhammad Asifzahoor. / Fractional processing-based active noise control algorithm for impulsive noise. 2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 10-14
@inproceedings{2e2774073a1f4e53915d0b6179b43154,
title = "Fractional processing-based active noise control algorithm for impulsive noise",
abstract = "This paper deals with active noise control (ANC) for impulsive noise sources for which the filtered-x least mean square (FxLMS) algorithm becomes unstable. By minimizing the fractional lower order moment, the resulting filtered-x least mean p-power (FxLMP) algorithm has an update vector being computed using sign operator and fractional power of the residual error signal. This results in improved robustness as compared with the FxLMS algorithm; however, the convergence speed is very slow. Improvement in convergence speed can be achieved by computing a fractional power for the error as well as for the (filtered) reference signal, combined with efficient normalization of the step-size parameter. This results in filtered-x modified generalized normalized Least mean p-power (FxMGNLMP) algorithm. In this paper we develop a new fractional processing-based adaptive algorithm for ANC of impulsive noise sources. The main idea is to compute a modified update vector for FxMGNLMP algorithm by computing fractional power of the tap-weight vector, and add this update term (after including an appropriate scaling factor) to the original update equation of the FxMGNLMP algorithm. The results of computer simulations demonstrate improved performance of the proposed approach especially when the noise source is highly impulsive.",
keywords = "Active noise control, fractional LMS, fractional lower order moment (FLOM), generalized LMP algorithm, non-Gaussian stable processes",
author = "Akhtar, {Muhammad Tahir} and Raja, {Muhammad Asifzahoor}",
year = "2015",
month = "8",
day = "31",
doi = "10.1109/ChinaSIP.2015.7230352",
language = "English",
pages = "10--14",
booktitle = "2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

TY - GEN

T1 - Fractional processing-based active noise control algorithm for impulsive noise

AU - Akhtar, Muhammad Tahir

AU - Raja, Muhammad Asifzahoor

PY - 2015/8/31

Y1 - 2015/8/31

N2 - This paper deals with active noise control (ANC) for impulsive noise sources for which the filtered-x least mean square (FxLMS) algorithm becomes unstable. By minimizing the fractional lower order moment, the resulting filtered-x least mean p-power (FxLMP) algorithm has an update vector being computed using sign operator and fractional power of the residual error signal. This results in improved robustness as compared with the FxLMS algorithm; however, the convergence speed is very slow. Improvement in convergence speed can be achieved by computing a fractional power for the error as well as for the (filtered) reference signal, combined with efficient normalization of the step-size parameter. This results in filtered-x modified generalized normalized Least mean p-power (FxMGNLMP) algorithm. In this paper we develop a new fractional processing-based adaptive algorithm for ANC of impulsive noise sources. The main idea is to compute a modified update vector for FxMGNLMP algorithm by computing fractional power of the tap-weight vector, and add this update term (after including an appropriate scaling factor) to the original update equation of the FxMGNLMP algorithm. The results of computer simulations demonstrate improved performance of the proposed approach especially when the noise source is highly impulsive.

AB - This paper deals with active noise control (ANC) for impulsive noise sources for which the filtered-x least mean square (FxLMS) algorithm becomes unstable. By minimizing the fractional lower order moment, the resulting filtered-x least mean p-power (FxLMP) algorithm has an update vector being computed using sign operator and fractional power of the residual error signal. This results in improved robustness as compared with the FxLMS algorithm; however, the convergence speed is very slow. Improvement in convergence speed can be achieved by computing a fractional power for the error as well as for the (filtered) reference signal, combined with efficient normalization of the step-size parameter. This results in filtered-x modified generalized normalized Least mean p-power (FxMGNLMP) algorithm. In this paper we develop a new fractional processing-based adaptive algorithm for ANC of impulsive noise sources. The main idea is to compute a modified update vector for FxMGNLMP algorithm by computing fractional power of the tap-weight vector, and add this update term (after including an appropriate scaling factor) to the original update equation of the FxMGNLMP algorithm. The results of computer simulations demonstrate improved performance of the proposed approach especially when the noise source is highly impulsive.

KW - Active noise control

KW - fractional LMS

KW - fractional lower order moment (FLOM)

KW - generalized LMP algorithm

KW - non-Gaussian stable processes

UR - http://www.scopus.com/inward/record.url?scp=84957540557&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84957540557&partnerID=8YFLogxK

U2 - 10.1109/ChinaSIP.2015.7230352

DO - 10.1109/ChinaSIP.2015.7230352

M3 - Conference contribution

SP - 10

EP - 14

BT - 2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

ER -