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Wind noise suppression in filtered-x least mean squares-based active noise control systems.

Yijing ChuSipei ZhaoLongbiao HeFeng Niu
Published in: The Journal of the Acoustical Society of America (2023)
Wind noise is notorious for its detrimental impacts on audio devices. This letter evaluates the influence of wind noise on the active noise control performance of headphones in a wind tunnel, and the noise reduction is found to decrease with wind speeds. To improve the performance of noise control systems in windy environments, the filtered-x least mean squares algorithm is modified based on the total least squares technique, taking the characteristics of wind noise into account. Computer simulations with real-recorded data demonstrate that the proposed algorithm could improve the noise reduction by approximately 3 dB in windy conditions.
Keyphrases
  • air pollution
  • machine learning
  • deep learning
  • magnetic resonance
  • electronic health record
  • big data
  • monte carlo