Fractional lower order moment based adaptive algorithms for active noise control of impulsive noise sources

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Abstract

This letter deals with active noise control (ANC) for impulsive noise sources being modeled using non-Gaussian stable process. The filtered-x least mean square algorithm is based on minimization of the variance of the error signal and becomes unstable for impulsive noise. The filtered-x least mean p-power algorithm-based on minimizing the fractional lower order moment-gives a robust performance for impulsive ANC; however, its convergence speed is very slow. This letter proposes modifying and employing a generalized normalized LMP algorithm for impulsive ANC. Extensive simulations are carried out which demonstrate the effectiveness of the proposed algorithm.

Original languageEnglish
Pages (from-to)EL456-62
JournalJournal of the Acoustical Society of America
Volume132
Issue number6
DOIs
Publication statusPublished - Dec 2012

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moments
error signals
optimization
simulation
Letters
Simulation

Keywords

  • Acoustics
  • Algorithms
  • Computer Simulation
  • Least-Squares Analysis
  • Models, Theoretical
  • Noise/prevention & control
  • Signal Processing, Computer-Assisted

Cite this

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abstract = "This letter deals with active noise control (ANC) for impulsive noise sources being modeled using non-Gaussian stable process. The filtered-x least mean square algorithm is based on minimization of the variance of the error signal and becomes unstable for impulsive noise. The filtered-x least mean p-power algorithm-based on minimizing the fractional lower order moment-gives a robust performance for impulsive ANC; however, its convergence speed is very slow. This letter proposes modifying and employing a generalized normalized LMP algorithm for impulsive ANC. Extensive simulations are carried out which demonstrate the effectiveness of the proposed algorithm.",
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AB - This letter deals with active noise control (ANC) for impulsive noise sources being modeled using non-Gaussian stable process. The filtered-x least mean square algorithm is based on minimization of the variance of the error signal and becomes unstable for impulsive noise. The filtered-x least mean p-power algorithm-based on minimizing the fractional lower order moment-gives a robust performance for impulsive ANC; however, its convergence speed is very slow. This letter proposes modifying and employing a generalized normalized LMP algorithm for impulsive ANC. Extensive simulations are carried out which demonstrate the effectiveness of the proposed algorithm.

KW - Acoustics

KW - Algorithms

KW - Computer Simulation

KW - Least-Squares Analysis

KW - Models, Theoretical

KW - Noise/prevention & control

KW - Signal Processing, Computer-Assisted

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