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
적응형 필터를 사용한 적응형 잡음 제거는 신호 측정을 방해하는 잡음을 제거하는 알려진 방법입니다. 적응형 잡음 제거기는 윈도잉 프로세스를 통해 현재 상황을 기반으로 필터링을 수행합니다. 윈도우 함수의 모양은 잡음(기준 신호)이 통과하는 미지 시스템의 특성 변동에 대한 적응형 잡음 제거기의 추적 성능을 결정합니다. 그러나 적응 필터링 분야에서 윈도우 함수의 형태는 아직까지 구체적으로 고려되지 않았다. 본 연구에서는 윈도우 함수가 적응형 잡음 제거기에 미치는 영향을 수학적으로 다루며, 생체의학 신호 측정과 같이 오프라인 처리가 가능한 상황에서 윈도우 함수의 최적화 방법을 제안합니다. 또한 수치 실험을 통해 최적화된 창 함수의 타당성을 입증합니다.
Yusuke MATSUBARA
Aichi Prefectural University
Naohiro TODA
Aichi Prefectural University
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부
Yusuke MATSUBARA, Naohiro TODA, "Optimization of the Window Function in an Adaptive Noise Canceller" in IEICE TRANSACTIONS on Fundamentals,
vol. E101-A, no. 11, pp. 1854-1860, November 2018, doi: 10.1587/transfun.E101.A.1854.
Abstract: Adaptive noise cancellation using adaptive filters is a known method for removing noise that interferes with signal measurements. The adaptive noise canceller performs filtering based on the current situation through a windowing process. The shape of the window function determines the tracking performance of the adaptive noise canceller with respect to the fluctuation of the property of the unknown system that noise (reference signal) passes. However, the shape of the window function in the field of adaptive filtering has not yet been considered in detail. This study mathematically treats the effect of the window function on the adaptive noise canceller and proposes an optimization method for the window function in situations where offline processing can be performed, such as biomedical signal measurements. We also demonstrate the validity of the optimized window function through numerical experiments.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E101.A.1854/_p
부
@ARTICLE{e101-a_11_1854,
author={Yusuke MATSUBARA, Naohiro TODA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Optimization of the Window Function in an Adaptive Noise Canceller},
year={2018},
volume={E101-A},
number={11},
pages={1854-1860},
abstract={Adaptive noise cancellation using adaptive filters is a known method for removing noise that interferes with signal measurements. The adaptive noise canceller performs filtering based on the current situation through a windowing process. The shape of the window function determines the tracking performance of the adaptive noise canceller with respect to the fluctuation of the property of the unknown system that noise (reference signal) passes. However, the shape of the window function in the field of adaptive filtering has not yet been considered in detail. This study mathematically treats the effect of the window function on the adaptive noise canceller and proposes an optimization method for the window function in situations where offline processing can be performed, such as biomedical signal measurements. We also demonstrate the validity of the optimized window function through numerical experiments.},
keywords={},
doi={10.1587/transfun.E101.A.1854},
ISSN={1745-1337},
month={November},}
부
TY - JOUR
TI - Optimization of the Window Function in an Adaptive Noise Canceller
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1854
EP - 1860
AU - Yusuke MATSUBARA
AU - Naohiro TODA
PY - 2018
DO - 10.1587/transfun.E101.A.1854
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E101-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2018
AB - Adaptive noise cancellation using adaptive filters is a known method for removing noise that interferes with signal measurements. The adaptive noise canceller performs filtering based on the current situation through a windowing process. The shape of the window function determines the tracking performance of the adaptive noise canceller with respect to the fluctuation of the property of the unknown system that noise (reference signal) passes. However, the shape of the window function in the field of adaptive filtering has not yet been considered in detail. This study mathematically treats the effect of the window function on the adaptive noise canceller and proposes an optimization method for the window function in situations where offline processing can be performed, such as biomedical signal measurements. We also demonstrate the validity of the optimized window function through numerical experiments.
ER -