The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Kami mencadangkan pemodelan laluan maklum balas dalam talian dengan sistem kawalan hingar aktif (PIANC) jenis pra songsang untuk menjejak turun naik secara stabil dalam laluan maklum balas. Sistem kawalan hingar aktif (ANC) konvensional dengan asas penapis pemodelan laluan maklum balas dalam talian (FBPM) ditapis-x algoritma kuasa dua terkecil min (FxLMS). Dalam algoritma FxLMS, ralat FBPM mempengaruhi penapis kawalan, yang menghasilkan penapis anti hingar dan pemodelan laluan sekunder (SPM). Penapis kawalan menyimpang apabila ralat terlalu besar. Oleh itu, adalah sukar bagi algoritma FxLMS untuk mengesan laluan maklum balas tanpa perbezaan. Sebaliknya, pendekatan yang dicadangkan menumpu secara stabil kerana ralat penapis FBPM tidak mempengaruhi penapis kawalan pada sistem PIANC. Oleh itu, kaedah yang dicadangkan boleh mengurangkan bunyi semasa menjejaki laluan maklum balas. Kertas kerja ini mengesahkan keberkesanan kaedah yang dicadangkan melalui analisis penumpuan, simulasi komputer, dan pelaksanaan pemproses isyarat digital.
Keisuke OKANO
Tottori University
Naoto SASAOKA
Tottori University
Yoshio ITOH
Tottori University
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Salinan
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
Salinan
@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},}
Salinan
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 -