@inproceedings{b3bdfceee9d6412fba07f1fa4f6c4c10,
title = "A novel adaptive active noise control algorithm based on Tikhonov regularisation",
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.",
keywords = "active noise control, adaptive algorithms, Tikhonov regularization, affine projection algorithm",
author = "Iman Ardekani and Neda Sakhaee and Hamid Sharifzadeh and Bashar Barmada and Gerard Lovell",
year = "2019",
doi = "10.1117/12.2520450",
language = "English",
isbn = "9781510628359",
series = "Proceedings of SPIE",
publisher = "SPIE",
pages = "1107109--1--1107109--5",
editor = "Kezhi Mao and Xudong Jiang",
booktitle = "Tenth International Conference on Signal Processing Systems",
address = "United States",
note = "10th International Conference on Signal Processing Systems, ICSPS 2018 ; Conference date: 16-11-2018 Through 18-11-2018",
}