Abstract
In this paper we consider active noise control (ANC) of impulsive noise having peaky distribution with heavy tail. Such impulsive noise can be modeled using non-Gaussian stable process for which second order moments do not exist. The most famous filtered-x least mean square (FxLMS) algorithm for ANC systems is based on second order moment of error signal, and hence, becomes unstable for the impulsive noise. Recently we have proposed variants of the FxLMS algorithm where improved performance has been realized either by thresholding the input data or efficiently normalizing the step-size for adaptation. In the practical ANC systems, these thresholding parameters need to be estimated offline and cannot be updated during online operation of ANC systems. Furthermore, normalizing the steps-size for an impulsive noise source would essentially freeze the adaptation for very large impulses. In order to solve these problems, in this paper we propose a novel approach for ANC of impulsive noise sources. The proposed approach is based on data-reusing (DR) type adaptive algorithm. The main idea is to improve the stability by normalizing the step-size, and improve the convergence speed by reusing the data. The computer simulations are carried out to verify the effectiveness of the proposed algorithm.
| Original language | English |
|---|---|
| Title of host publication | 2013 IEEE 9th International Conference on Emerging Technologies, ICET 2013 |
| Publisher | IEEE Computer Society |
| ISBN (Print) | 9781479934560 |
| DOIs | |
| Publication status | Published - Jan 1 2013 |
| Event | 2013 IEEE 9th International Conference on Emerging Technologies, ICET 2013 - Islamabad, Pakistan Duration: Dec 9 2013 → Dec 10 2013 |
Conference
| Conference | 2013 IEEE 9th International Conference on Emerging Technologies, ICET 2013 |
|---|---|
| Country | Pakistan |
| City | Islamabad |
| Period | 12/9/13 → 12/10/13 |
Fingerprint
Keywords
- Active noise control
- Data-reusing algorithm
- impulsive noise
- normalized step-size
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Signal Processing
Cite this
Data-reusing-based adaptive algorithm for active noise control of impulsive noise sources. / Akhtar, Muhammad Tahir.
2013 IEEE 9th International Conference on Emerging Technologies, ICET 2013. IEEE Computer Society, 2013. 6743494.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Data-reusing-based adaptive algorithm for active noise control of impulsive noise sources
AU - Akhtar, Muhammad Tahir
PY - 2013/1/1
Y1 - 2013/1/1
N2 - In this paper we consider active noise control (ANC) of impulsive noise having peaky distribution with heavy tail. Such impulsive noise can be modeled using non-Gaussian stable process for which second order moments do not exist. The most famous filtered-x least mean square (FxLMS) algorithm for ANC systems is based on second order moment of error signal, and hence, becomes unstable for the impulsive noise. Recently we have proposed variants of the FxLMS algorithm where improved performance has been realized either by thresholding the input data or efficiently normalizing the step-size for adaptation. In the practical ANC systems, these thresholding parameters need to be estimated offline and cannot be updated during online operation of ANC systems. Furthermore, normalizing the steps-size for an impulsive noise source would essentially freeze the adaptation for very large impulses. In order to solve these problems, in this paper we propose a novel approach for ANC of impulsive noise sources. The proposed approach is based on data-reusing (DR) type adaptive algorithm. The main idea is to improve the stability by normalizing the step-size, and improve the convergence speed by reusing the data. The computer simulations are carried out to verify the effectiveness of the proposed algorithm.
AB - In this paper we consider active noise control (ANC) of impulsive noise having peaky distribution with heavy tail. Such impulsive noise can be modeled using non-Gaussian stable process for which second order moments do not exist. The most famous filtered-x least mean square (FxLMS) algorithm for ANC systems is based on second order moment of error signal, and hence, becomes unstable for the impulsive noise. Recently we have proposed variants of the FxLMS algorithm where improved performance has been realized either by thresholding the input data or efficiently normalizing the step-size for adaptation. In the practical ANC systems, these thresholding parameters need to be estimated offline and cannot be updated during online operation of ANC systems. Furthermore, normalizing the steps-size for an impulsive noise source would essentially freeze the adaptation for very large impulses. In order to solve these problems, in this paper we propose a novel approach for ANC of impulsive noise sources. The proposed approach is based on data-reusing (DR) type adaptive algorithm. The main idea is to improve the stability by normalizing the step-size, and improve the convergence speed by reusing the data. The computer simulations are carried out to verify the effectiveness of the proposed algorithm.
KW - Active noise control
KW - Data-reusing algorithm
KW - impulsive noise
KW - normalized step-size
UR - http://www.scopus.com/inward/record.url?scp=84896788137&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84896788137&partnerID=8YFLogxK
U2 - 10.1109/ICET.2013.6743494
DO - 10.1109/ICET.2013.6743494
M3 - Conference contribution
AN - SCOPUS:84896788137
SN - 9781479934560
BT - 2013 IEEE 9th International Conference on Emerging Technologies, ICET 2013
PB - IEEE Computer Society
ER -