Robust Frequency-Domain Recursive Least M-Estimate Adaptive Filter for Acoustic System Identification

Hongsen He; Jingdong Chen; Jacob Benesty; Yi Yu

doi:10.1109/ICASSP40776.2020.9054296

Robust Frequency-Domain Recursive Least M-Estimate Adaptive Filter for Acoustic System Identification

Hongsen He, Jingdong Chen, Jacob Benesty, Yi Yu

航海学院

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

4 引用（Scopus）

摘要

To identify acoustic systems in non-Gaussian and Gaussian noises, a robust frequency-domain recursive least M-estimate (FRLM) adaptive filtering algorithm is proposed. The cost function of the adaptive filter is defined by using a robust time-domain M-estimator, while its update equation is derived from the normal equation in the frequency domain. As compared to the frequency-domain recursive least-squares adaptive filter, the FRLM algorithm obtains the robustness to non-Gaussian and Gaussian noises. The performance of the proposed algorithm is validated in simulated acoustic environments.

源语言	英语
主期刊名	2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
出版商	Institute of Electrical and Electronics Engineers Inc.
页	471-475
页数	5
ISBN（电子版）	9781509066315
DOI	https://doi.org/10.1109/ICASSP40776.2020.9054296
出版状态	已出版 - 5月 2020
活动	2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, 西班牙期限: 4 5月 2020 → 8 5月 2020

出版系列

姓名	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
卷	2020-May
ISSN（印刷版）	1520-6149

会议

会议	2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
国家/地区	西班牙
市	Barcelona
时期	4/05/20 → 8/05/20

访问文件

10.1109/ICASSP40776.2020.9054296

其它文件与链接

链接到 Scopus 的出版物

引用此

He, H., Chen, J., Benesty, J., & Yu, Y. (2020). Robust Frequency-Domain Recursive Least M-Estimate Adaptive Filter for Acoustic System Identification. 在 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings (页码 471-475). 文章 9054296 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; 卷 2020-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP40776.2020.9054296

He, Hongsen ; Chen, Jingdong ; Benesty, Jacob 等. / Robust Frequency-Domain Recursive Least M-Estimate Adaptive Filter for Acoustic System Identification. 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. 页码 471-475 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

@inproceedings{747810e02f7a43eab1468ab32f38f42a,

title = "Robust Frequency-Domain Recursive Least M-Estimate Adaptive Filter for Acoustic System Identification",

abstract = "To identify acoustic systems in non-Gaussian and Gaussian noises, a robust frequency-domain recursive least M-estimate (FRLM) adaptive filtering algorithm is proposed. The cost function of the adaptive filter is defined by using a robust time-domain M-estimator, while its update equation is derived from the normal equation in the frequency domain. As compared to the frequency-domain recursive least-squares adaptive filter, the FRLM algorithm obtains the robustness to non-Gaussian and Gaussian noises. The performance of the proposed algorithm is validated in simulated acoustic environments.",

keywords = "Acoustic system identification, frequency-domain adaptive filter, recursive least M-estimate, robustness",

author = "Hongsen He and Jingdong Chen and Jacob Benesty and Yi Yu",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 ; Conference date: 04-05-2020 Through 08-05-2020",

year = "2020",

month = may,

doi = "10.1109/ICASSP40776.2020.9054296",

language = "英语",

series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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He, H, Chen, J, Benesty, J & Yu, Y 2020, Robust Frequency-Domain Recursive Least M-Estimate Adaptive Filter for Acoustic System Identification. 在 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings., 9054296, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 卷 2020-May, Institute of Electrical and Electronics Engineers Inc., 页码 471-475, 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020, Barcelona, 西班牙, 4/05/20. https://doi.org/10.1109/ICASSP40776.2020.9054296

Robust Frequency-Domain Recursive Least M-Estimate Adaptive Filter for Acoustic System Identification. / He, Hongsen; Chen, Jingdong; Benesty, Jacob 等.
2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. 页码 471-475 9054296 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; 卷 2020-May).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Robust Frequency-Domain Recursive Least M-Estimate Adaptive Filter for Acoustic System Identification

AU - He, Hongsen

AU - Chen, Jingdong

AU - Benesty, Jacob

AU - Yu, Yi

PY - 2020/5

Y1 - 2020/5

N2 - To identify acoustic systems in non-Gaussian and Gaussian noises, a robust frequency-domain recursive least M-estimate (FRLM) adaptive filtering algorithm is proposed. The cost function of the adaptive filter is defined by using a robust time-domain M-estimator, while its update equation is derived from the normal equation in the frequency domain. As compared to the frequency-domain recursive least-squares adaptive filter, the FRLM algorithm obtains the robustness to non-Gaussian and Gaussian noises. The performance of the proposed algorithm is validated in simulated acoustic environments.

AB - To identify acoustic systems in non-Gaussian and Gaussian noises, a robust frequency-domain recursive least M-estimate (FRLM) adaptive filtering algorithm is proposed. The cost function of the adaptive filter is defined by using a robust time-domain M-estimator, while its update equation is derived from the normal equation in the frequency domain. As compared to the frequency-domain recursive least-squares adaptive filter, the FRLM algorithm obtains the robustness to non-Gaussian and Gaussian noises. The performance of the proposed algorithm is validated in simulated acoustic environments.

KW - Acoustic system identification

KW - frequency-domain adaptive filter

KW - recursive least M-estimate

KW - robustness

UR - http://www.scopus.com/inward/record.url?scp=85089238743&partnerID=8YFLogxK

U2 - 10.1109/ICASSP40776.2020.9054296

DO - 10.1109/ICASSP40776.2020.9054296

M3 - 会议稿件

AN - SCOPUS:85089238743

T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

SP - 471

EP - 475

BT - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020

Y2 - 4 May 2020 through 8 May 2020

ER -

He H, Chen J, Benesty J, Yu Y. Robust Frequency-Domain Recursive Least M-Estimate Adaptive Filter for Acoustic System Identification. 在 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. 页码 471-475. 9054296. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP40776.2020.9054296

Robust Frequency-Domain Recursive Least M-Estimate Adaptive Filter for Acoustic System Identification

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