Maximum a posteriori adjustment of adaptive transversal filters in active noise control
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Authors
Ardekani, Iman
Zhang, X.
Sharifzadeh, Hamid
Kaipio, J.
Zhang, X.
Sharifzadeh, Hamid
Kaipio, J.
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Date
2017-12
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Conference Contribution - Paper in Published Proceedings
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
FxLMS algorithm
active noise control (ANC)
noise control
white Gaussian process
white noise
pink noise
ANC
active noise control (ANC)
noise control
white Gaussian process
white noise
pink noise
ANC
ANZSRC Field of Research Code (2020)
Citation
Ardekani, I. T., Zhang, X., Sharifzadeh, H., & Kaipio, J. (2017, December). Maximum a posteriori adjustment of adaptive transversal filters in active noise control. APSIPA (Ed.), Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA 2017) 1, 1-6 pp.
Abstract
This paper develops a novel approach to adaptive active noise control based on the theory of Bayesian estimation. Control system parameters are considered as statistical variables and a formulation for the joint probability density function of them is derived. An optimal solution for the system parameters is then calculated through maximizing the density function. An efficient adaptive algorithm for iterative calculation of the optimal parameters is proposed. It is shown that the well known FxLMS algorithm can be derived as a special case of the proposed algorithm, where the noise to be canceled is a white Gaussian process. Simulation results verify the preference of the proposed system to the traditional active noise control systems in terms of steady-state performance and convergence rate. It is also shown that the preference of the proposed system is much more evident when the noise to be canceled is not white. Finally, a successful implementation of the proposed system in an experimental acoustic duct is reported.
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