A novel adaptive active noise control algorithm based on Tikhonov regularisation
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Authors
Ardekani, Iman
Sakhaee, N.
Sharifzadeh, Hamid
Barmada, Bashar
Lovell, G.
Sakhaee, N.
Sharifzadeh, Hamid
Barmada, Bashar
Lovell, G.
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Date
2018-11
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Conference Contribution - Paper in Published Proceedings
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active noise control (ANC)
adaptive algorithms
Tikhonov regularization
affine projection algorithm
adaptive algorithms
Tikhonov regularization
affine projection algorithm
ANZSRC Field of Research Code (2020)
Citation
Ardekani, I., Sakhaee, N., Sharifzadeh, H., Barmada, B., & Lovell, G. (2018). A novel adaptive active noise control algorithm based on Tikhonov regularisation. 10th International Conference on Signal Processing Systems (ICSPS 2018). (pp. 1-5). Retrieved from http://www.icsps.org/
Abstract
This paper proposes a novel adaptive active noise control algorithm based on Tikhonov regularization theory. A regularized cost function consisting of the weighted sum of the most recent samples of the residual noise and its derivative is defined. By setting the gradient vector of the cost function to zero, an optimal solution for the control parameters is obtained. Based on the proposed optimal solution, a computationally efficient algorithm for adaptive adjustment of the control parameters is developed. It is shown that the regularized affine projection algorithm can be considered as a very special case of the proposed algorithm. Different computer simulation experiments show the validity and efficiency of the proposed algorithm.
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