Abstract
The main objective of active noise control (ANC) is to provide attenuation for the environmental acoustic noise. The adaptive algorithms for ANC systems work well to attenuate the Gaussian noise; however, their performance may degrade for non-Gaussian impulsive noise sources. Recently, we have proposed variants of the most famous ANC algorithm, the filtered-x least mean square (FxLMS) algorithm, where an improved performance has been realized by thresholding the input data or by efficiently normalizing the step-size. In this paper, we propose a modified binormalized data-reusing (BNDR)-based adaptive algorithm for impulsive ANC. The proposed algorithm is derived by minimizing a modified cost function, and is based on reusing the past and present samples of data. The main contribution of the paper is to develop a practical DR-type adaptive algorithm, which incorporates an efficiently normalized step-size, and is well suited for ANC of impulsive noise sources. The computer simulations are carried out to demonstrate the effectiveness of the proposed algorithm. It is shown that an improved performance has been realized with a reasonable increase in the computational complexity.
Original language | English |
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Pages (from-to) | 56-64 |
Number of pages | 9 |
Journal | Digital Signal Processing: A Review Journal |
Volume | 49 |
DOIs | |
Publication status | Published - Feb 1 2016 |
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Keywords
- Active noise control
- Adaptive algorithm
- Binormalized data-reusing
- Impulsive noise
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
Cite this
Binormalized data-reusing adaptive filtering algorithm for active control of impulsive sources. / Akhtar, Muhammad Tahir.
In: Digital Signal Processing: A Review Journal, Vol. 49, 01.02.2016, p. 56-64.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Binormalized data-reusing adaptive filtering algorithm for active control of impulsive sources
AU - Akhtar, Muhammad Tahir
PY - 2016/2/1
Y1 - 2016/2/1
N2 - The main objective of active noise control (ANC) is to provide attenuation for the environmental acoustic noise. The adaptive algorithms for ANC systems work well to attenuate the Gaussian noise; however, their performance may degrade for non-Gaussian impulsive noise sources. Recently, we have proposed variants of the most famous ANC algorithm, the filtered-x least mean square (FxLMS) algorithm, where an improved performance has been realized by thresholding the input data or by efficiently normalizing the step-size. In this paper, we propose a modified binormalized data-reusing (BNDR)-based adaptive algorithm for impulsive ANC. The proposed algorithm is derived by minimizing a modified cost function, and is based on reusing the past and present samples of data. The main contribution of the paper is to develop a practical DR-type adaptive algorithm, which incorporates an efficiently normalized step-size, and is well suited for ANC of impulsive noise sources. The computer simulations are carried out to demonstrate the effectiveness of the proposed algorithm. It is shown that an improved performance has been realized with a reasonable increase in the computational complexity.
AB - The main objective of active noise control (ANC) is to provide attenuation for the environmental acoustic noise. The adaptive algorithms for ANC systems work well to attenuate the Gaussian noise; however, their performance may degrade for non-Gaussian impulsive noise sources. Recently, we have proposed variants of the most famous ANC algorithm, the filtered-x least mean square (FxLMS) algorithm, where an improved performance has been realized by thresholding the input data or by efficiently normalizing the step-size. In this paper, we propose a modified binormalized data-reusing (BNDR)-based adaptive algorithm for impulsive ANC. The proposed algorithm is derived by minimizing a modified cost function, and is based on reusing the past and present samples of data. The main contribution of the paper is to develop a practical DR-type adaptive algorithm, which incorporates an efficiently normalized step-size, and is well suited for ANC of impulsive noise sources. The computer simulations are carried out to demonstrate the effectiveness of the proposed algorithm. It is shown that an improved performance has been realized with a reasonable increase in the computational complexity.
KW - Active noise control
KW - Adaptive algorithm
KW - Binormalized data-reusing
KW - Impulsive noise
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U2 - 10.1016/j.dsp.2015.11.002
DO - 10.1016/j.dsp.2015.11.002
M3 - Article
AN - SCOPUS:84951325855
VL - 49
SP - 56
EP - 64
JO - Digital Signal Processing: A Review Journal
JF - Digital Signal Processing: A Review Journal
SN - 1051-2004
ER -