Frequency Domain Adaptive Algorithm for Active Noise Control (1st Report, Proposal of an Algorithm and Computer Simulations)

Shinya Kijimoto, Hiroshi Shimojima

Research output: Contribution to journalArticle

Abstract

A new adaptive control algorithm in frequency domain was proposed. This frequency domain approach corresponds to the ordinary filtered-x least mean square (LMS) algorithm in discrete time domain. In this approach, the fast Fourier transform (FFT) was used for converting signals between frequency domain and discrete time domain. Since the computaion processes in these two domains are almost independent with each other, this algorithm can be realized effectively by using two processors. Computer simulations were carried out for investigating convergence characteristics of this approach. As the result of these simulations, it was shown that this algorithm has faster convergence with less computation comparing to the ordinary filtered-x LMS algorithm.

Original languageEnglish
Pages (from-to)3581-3586
Number of pages6
Journaltransactions of the japan society of mechanical engineers series c
Volume61
Issue number589
DOIs
Publication statusPublished - Jan 1 1995

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Active noise control
Adaptive algorithms
Computer simulation
Fast Fourier transforms

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

Cite this

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abstract = "A new adaptive control algorithm in frequency domain was proposed. This frequency domain approach corresponds to the ordinary filtered-x least mean square (LMS) algorithm in discrete time domain. In this approach, the fast Fourier transform (FFT) was used for converting signals between frequency domain and discrete time domain. Since the computaion processes in these two domains are almost independent with each other, this algorithm can be realized effectively by using two processors. Computer simulations were carried out for investigating convergence characteristics of this approach. As the result of these simulations, it was shown that this algorithm has faster convergence with less computation comparing to the ordinary filtered-x LMS algorithm.",
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