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.
Yusuke MATSUBARA
Aichi Prefectural University
Naohiro TODA
Aichi Prefectural University
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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
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@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},}
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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 -