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Active noise cancellation of variable frequency narrow band noise using mixture of RLS and LMS algorithms

Active noise cancellation of variable frequency narrow band noise using mixture of RLS and LMS... Due to the good tracking behaviour of the LMS adaptive filter in a noisy environment, the FX-LMS algorithm is proposed in the literature as a method of active noise control, ANC. But each of the LMS and RLS algorithms have their own advantages and disadvantages. In this paper, a new approach based on a mixture of the RLS and LMS algorithms, RLMS, is presented. The optimum weights of the mixture are derived and it is proved that the MMSE of the proposed system is reduced compared to those of the RLS and LMS algorithms. Then, the proposed RLMS algorithm is employed for active noise cancellation to form the FX-RLMS algorithm, in a duct. Experimental results show better performance of the RLMS algorithm compared to both the RLS and LMS algorithms of convergence and tracking behaviour in the system identification problem and noisy chirp tracking. The FX-RLMS algorithm shows better results in active noise cancellation compared to the FX-LMS algorithm. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Signal and Imaging Systems Engineering Inderscience Publishers

Active noise cancellation of variable frequency narrow band noise using mixture of RLS and LMS algorithms

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References (41)

Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1748-0698
eISSN
1748-0701
DOI
10.1504/IJSISE.2009.033757
Publisher site
See Article on Publisher Site

Abstract

Due to the good tracking behaviour of the LMS adaptive filter in a noisy environment, the FX-LMS algorithm is proposed in the literature as a method of active noise control, ANC. But each of the LMS and RLS algorithms have their own advantages and disadvantages. In this paper, a new approach based on a mixture of the RLS and LMS algorithms, RLMS, is presented. The optimum weights of the mixture are derived and it is proved that the MMSE of the proposed system is reduced compared to those of the RLS and LMS algorithms. Then, the proposed RLMS algorithm is employed for active noise cancellation to form the FX-RLMS algorithm, in a duct. Experimental results show better performance of the RLMS algorithm compared to both the RLS and LMS algorithms of convergence and tracking behaviour in the system identification problem and noisy chirp tracking. The FX-RLMS algorithm shows better results in active noise cancellation compared to the FX-LMS algorithm.

Journal

International Journal of Signal and Imaging Systems EngineeringInderscience Publishers

Published: Jan 1, 2009

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