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PreprintCC BY-NC 4.0HAL

Accelerating adaptive feedback noise attenuators using a dynamic adaptation gain

  • Tudor-Bogdan Airimitoaie
  • Ioan Doré Landau
  • Gabriel Buche
  • Bernard Vau
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Abstract

The paper presents the use of dynamic adaptation gain/learning rate (DAG) for accelerating the direct adaptive feedback noise attenuation schemes using a Youla-Kučera parametrization for the feedback controller. The DAG is an ARMA (poles-zeros) filter embedded in the gradient type adaptation/learning algorithms (it filters the gradient or its approximation). Through relevant experiments, the paper will show that significant acceleration of the adaptive transients is also obtained in the case of direct adaptive feedback noise attenuators.

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Cite

BibTeXRIS
BibTeX
@misc{airimitoaie2026accelerating,
  title = {{Accelerating adaptive feedback noise attenuators using a dynamic adaptation gain}},
  author = {Tudor-Bogdan Airimitoaie and Ioan Doré Landau and Gabriel Buche and Bernard Vau},
  howpublished = {HAL},
  year = {2026},
  month = oct,
  url = {https://hal.science/hal-05828319v1},
  note = {CC BY-NC 4.0},
}
RIS
TY  - UNPB
TI  - Accelerating adaptive feedback noise attenuators using a dynamic adaptation gain
AU  - Tudor-Bogdan Airimitoaie
AU  - Ioan Doré Landau
AU  - Gabriel Buche
AU  - Bernard Vau
PY  - 2026
DA  - 2026/10/07
PB  - HAL
UR  - https://hal.science/hal-05828319v1
AB  - The paper presents the use of dynamic adaptation gain/learning rate (DAG) for accelerating the direct adaptive feedback noise attenuation schemes using a Youla-Kučera parametrization for the feedback controller. The DAG is an ARMA (poles-zeros) filter embedded in the gradient type adaptation/learning algorithms (it filters the gradient or its approximation). Through relevant experiments, the paper will show that significant acceleration of the adaptive transients is also obtained in the case of direct adaptive feedback noise attenuators.
ER  -