Feedback Path-Tracking Pre-Inverse Type Active Noise Control
Summary :
We propose online feedback path modeling with a pre-inverse type active noise control (PIANC) system to track the fluctuation stably in the feedback path. The conventional active noise control (ANC) system with online feedback path modeling (FBPM) filter bases filtered-x least mean square (FxLMS) algorithm. In the FxLMS algorithm, the error of FBPM influences a control filter, which generates an anti-noise, and secondary path modeling (SPM) filter. The control filter diverges when the error is too large. Therefore, it is difficult for the FxLMS algorithm to track the feedback path without divergence. On the other hand, the proposed approach converges stably because the FBPM filter's error does not influence a control filter on the PIANC system. Thus, the proposed method can reduce noise while tracking the feedback path. This paper verified the effectiveness of the proposed method by convergence analysis, computer simulation, and implementation of a digital signal processor.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E104-A No.7 pp.954-961
- Publication Date
- 2021/07/01
- Publicized
- 2020/12/28
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.2020EAP1081
- Type of Manuscript
- PAPER
- Category
- Digital Signal Processing
Authors
Keisuke OKANO
Tottori University
Naoto SASAOKA
Tottori University
Yoshio ITOH
Tottori University
Keyword
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Keisuke OKANO, Naoto SASAOKA, Yoshio ITOH, "Feedback Path-Tracking Pre-Inverse Type Active Noise Control" in IEICE TRANSACTIONS on Fundamentals,
vol. E104-A, no. 7, pp. 954-961, July 2021, doi: 10.1587/transfun.2020EAP1081.
Abstract: We propose online feedback path modeling with a pre-inverse type active noise control (PIANC) system to track the fluctuation stably in the feedback path. The conventional active noise control (ANC) system with online feedback path modeling (FBPM) filter bases filtered-x least mean square (FxLMS) algorithm. In the FxLMS algorithm, the error of FBPM influences a control filter, which generates an anti-noise, and secondary path modeling (SPM) filter. The control filter diverges when the error is too large. Therefore, it is difficult for the FxLMS algorithm to track the feedback path without divergence. On the other hand, the proposed approach converges stably because the FBPM filter's error does not influence a control filter on the PIANC system. Thus, the proposed method can reduce noise while tracking the feedback path. This paper verified the effectiveness of the proposed method by convergence analysis, computer simulation, and implementation of a digital signal processor.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2020EAP1081/_p
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@ARTICLE{e104-a_7_954,
author={Keisuke OKANO, Naoto SASAOKA, Yoshio ITOH, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Feedback Path-Tracking Pre-Inverse Type Active Noise Control},
year={2021},
volume={E104-A},
number={7},
pages={954-961},
abstract={We propose online feedback path modeling with a pre-inverse type active noise control (PIANC) system to track the fluctuation stably in the feedback path. The conventional active noise control (ANC) system with online feedback path modeling (FBPM) filter bases filtered-x least mean square (FxLMS) algorithm. In the FxLMS algorithm, the error of FBPM influences a control filter, which generates an anti-noise, and secondary path modeling (SPM) filter. The control filter diverges when the error is too large. Therefore, it is difficult for the FxLMS algorithm to track the feedback path without divergence. On the other hand, the proposed approach converges stably because the FBPM filter's error does not influence a control filter on the PIANC system. Thus, the proposed method can reduce noise while tracking the feedback path. This paper verified the effectiveness of the proposed method by convergence analysis, computer simulation, and implementation of a digital signal processor.},
keywords={},
doi={10.1587/transfun.2020EAP1081},
ISSN={1745-1337},
month={July},}
Copy
TY - JOUR
TI - Feedback Path-Tracking Pre-Inverse Type Active Noise Control
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 954
EP - 961
AU - Keisuke OKANO
AU - Naoto SASAOKA
AU - Yoshio ITOH
PY - 2021
DO - 10.1587/transfun.2020EAP1081
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E104-A
IS - 7
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - July 2021
AB - We propose online feedback path modeling with a pre-inverse type active noise control (PIANC) system to track the fluctuation stably in the feedback path. The conventional active noise control (ANC) system with online feedback path modeling (FBPM) filter bases filtered-x least mean square (FxLMS) algorithm. In the FxLMS algorithm, the error of FBPM influences a control filter, which generates an anti-noise, and secondary path modeling (SPM) filter. The control filter diverges when the error is too large. Therefore, it is difficult for the FxLMS algorithm to track the feedback path without divergence. On the other hand, the proposed approach converges stably because the FBPM filter's error does not influence a control filter on the PIANC system. Thus, the proposed method can reduce noise while tracking the feedback path. This paper verified the effectiveness of the proposed method by convergence analysis, computer simulation, and implementation of a digital signal processor.
ER -
English
