IEICE TRANSACTIONS on Information
An Effective Acoustic Feedback Cancellation Algorithm Based on the Normalized Sub-Band Adaptive Filter
Summary :
In this letter, an effective acoustic feedback cancellation algorithm is proposed based on the normalized sub-band adaptive filter (NSAF). To improve the confliction between fast convergence rate and low misalignment in the NSAF algorithm, a variable step size is designed to automatically vary according to the update state of the filter. The update state of the filter is adaptively detected via the normalized distance between the long term average and the short term average of the tap-weight vector. Simulation results demonstrate that the proposed algorithm has superior performance in terms of convergence rate and misalignment.
- Publication
- IEICE TRANSACTIONS on Information Vol.E99-D No.1 pp.288-291
- Publication Date
- 2016/01/01
- Publicized
- 2015/10/20
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2015EDL8087
- Type of Manuscript
- LETTER
- Category
- Speech and Hearing
Authors
Xia WANG
Southeast University
Ruiyu LIANG
Nanjing Institute of Technology
Qingyun WANG
Nanjing Institute of Technology
Li ZHAO
Southeast University
Cairong ZOU
Southeast University
Keyword
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Xia WANG, Ruiyu LIANG, Qingyun WANG, Li ZHAO, Cairong ZOU, "An Effective Acoustic Feedback Cancellation Algorithm Based on the Normalized Sub-Band Adaptive Filter" in IEICE TRANSACTIONS on Information,
vol. E99-D, no. 1, pp. 288-291, January 2016, doi: 10.1587/transinf.2015EDL8087.
Abstract: In this letter, an effective acoustic feedback cancellation algorithm is proposed based on the normalized sub-band adaptive filter (NSAF). To improve the confliction between fast convergence rate and low misalignment in the NSAF algorithm, a variable step size is designed to automatically vary according to the update state of the filter. The update state of the filter is adaptively detected via the normalized distance between the long term average and the short term average of the tap-weight vector. Simulation results demonstrate that the proposed algorithm has superior performance in terms of convergence rate and misalignment.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2015EDL8087/_p
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@ARTICLE{e99-d_1_288,
author={Xia WANG, Ruiyu LIANG, Qingyun WANG, Li ZHAO, Cairong ZOU, },
journal={IEICE TRANSACTIONS on Information},
title={An Effective Acoustic Feedback Cancellation Algorithm Based on the Normalized Sub-Band Adaptive Filter},
year={2016},
volume={E99-D},
number={1},
pages={288-291},
abstract={In this letter, an effective acoustic feedback cancellation algorithm is proposed based on the normalized sub-band adaptive filter (NSAF). To improve the confliction between fast convergence rate and low misalignment in the NSAF algorithm, a variable step size is designed to automatically vary according to the update state of the filter. The update state of the filter is adaptively detected via the normalized distance between the long term average and the short term average of the tap-weight vector. Simulation results demonstrate that the proposed algorithm has superior performance in terms of convergence rate and misalignment.},
keywords={},
doi={10.1587/transinf.2015EDL8087},
ISSN={1745-1361},
month={January},}
Copy
TY - JOUR
TI - An Effective Acoustic Feedback Cancellation Algorithm Based on the Normalized Sub-Band Adaptive Filter
T2 - IEICE TRANSACTIONS on Information
SP - 288
EP - 291
AU - Xia WANG
AU - Ruiyu LIANG
AU - Qingyun WANG
AU - Li ZHAO
AU - Cairong ZOU
PY - 2016
DO - 10.1587/transinf.2015EDL8087
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2016
AB - In this letter, an effective acoustic feedback cancellation algorithm is proposed based on the normalized sub-band adaptive filter (NSAF). To improve the confliction between fast convergence rate and low misalignment in the NSAF algorithm, a variable step size is designed to automatically vary according to the update state of the filter. The update state of the filter is adaptively detected via the normalized distance between the long term average and the short term average of the tap-weight vector. Simulation results demonstrate that the proposed algorithm has superior performance in terms of convergence rate and misalignment.
ER -
English
