Adaptive Cancelling for Frequency-Fluctuating Periodic Interference

Yusuke MATSUBARA; Naohiro TODA

doi:10.1587/transinf.2016EDP7317

Adaptive Cancelling for Frequency-Fluctuating Periodic Interference

Yusuke MATSUBARA, Naohiro TODA

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Summary :

Periodic interference frequently affects the measurement of small signals and causes problems in clinical diagnostics. Adaptive filters can be used as potential tools for cancelling such interference. However, when the interference has a frequency fluctuation, the ideal adaptive-filter coefficients for cancelling the interference also fluctuate. When the adaptation property of the algorithm is slow compared with the frequency fluctuation, the interference-cancelling performance is degraded. However, if the adaptation is too quick, the performance is degraded owing to the target signal. To overcome this problem, we propose an adaptive filter that suppresses the fluctuation of the ideal coefficients by utilizing a $rac{pi}{2}$ phase-delay device. This method assumes a frequency response that characterizes the transmission path from the interference source to the main input signal to be sufficiently smooth. In the numerical examples, the proposed method exhibits good performance in the presence of a frequency fluctuation when the forgetting factor is large. Moreover, we show that the proposed method reduces the calculation cost.

Publication: IEICE TRANSACTIONS on Information Vol.E100-D No.2 pp.359-366

Publication Date: 2017/02/01

Publicized: 2016/11/18

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2016EDP7317

Type of Manuscript: PAPER

Category: Biological Engineering

Authors

Yusuke MATSUBARA
Aichi Prefectural University
Naohiro TODA
Aichi Prefectural University

Keyword

periodic interference, adaptive filter, RLS algorithm, frequency fluctuation, higher harmonic

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Yusuke MATSUBARA, Naohiro TODA, "Adaptive Cancelling for Frequency-Fluctuating Periodic Interference" in IEICE TRANSACTIONS on Information, vol. E100-D, no. 2, pp. 359-366, February 2017, doi: 10.1587/transinf.2016EDP7317.
Abstract: Periodic interference frequently affects the measurement of small signals and causes problems in clinical diagnostics. Adaptive filters can be used as potential tools for cancelling such interference. However, when the interference has a frequency fluctuation, the ideal adaptive-filter coefficients for cancelling the interference also fluctuate. When the adaptation property of the algorithm is slow compared with the frequency fluctuation, the interference-cancelling performance is degraded. However, if the adaptation is too quick, the performance is degraded owing to the target signal. To overcome this problem, we propose an adaptive filter that suppresses the fluctuation of the ideal coefficients by utilizing a $rac{pi}{2}$ phase-delay device. This method assumes a frequency response that characterizes the transmission path from the interference source to the main input signal to be sufficiently smooth. In the numerical examples, the proposed method exhibits good performance in the presence of a frequency fluctuation when the forgetting factor is large. Moreover, we show that the proposed method reduces the calculation cost.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2016EDP7317/_p

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@ARTICLE{e100-d_2_359,
author={Yusuke MATSUBARA, Naohiro TODA, },
journal={IEICE TRANSACTIONS on Information},
title={Adaptive Cancelling for Frequency-Fluctuating Periodic Interference},
year={2017},
volume={E100-D},
number={2},
pages={359-366},
abstract={Periodic interference frequently affects the measurement of small signals and causes problems in clinical diagnostics. Adaptive filters can be used as potential tools for cancelling such interference. However, when the interference has a frequency fluctuation, the ideal adaptive-filter coefficients for cancelling the interference also fluctuate. When the adaptation property of the algorithm is slow compared with the frequency fluctuation, the interference-cancelling performance is degraded. However, if the adaptation is too quick, the performance is degraded owing to the target signal. To overcome this problem, we propose an adaptive filter that suppresses the fluctuation of the ideal coefficients by utilizing a $rac{pi}{2}$ phase-delay device. This method assumes a frequency response that characterizes the transmission path from the interference source to the main input signal to be sufficiently smooth. In the numerical examples, the proposed method exhibits good performance in the presence of a frequency fluctuation when the forgetting factor is large. Moreover, we show that the proposed method reduces the calculation cost.},
keywords={},
doi={10.1587/transinf.2016EDP7317},
ISSN={1745-1361},
month={February},}

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TY - JOUR
TI - Adaptive Cancelling for Frequency-Fluctuating Periodic Interference
T2 - IEICE TRANSACTIONS on Information
SP - 359
EP - 366
AU - Yusuke MATSUBARA
AU - Naohiro TODA
PY - 2017
DO - 10.1587/transinf.2016EDP7317
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E100-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2017
AB - Periodic interference frequently affects the measurement of small signals and causes problems in clinical diagnostics. Adaptive filters can be used as potential tools for cancelling such interference. However, when the interference has a frequency fluctuation, the ideal adaptive-filter coefficients for cancelling the interference also fluctuate. When the adaptation property of the algorithm is slow compared with the frequency fluctuation, the interference-cancelling performance is degraded. However, if the adaptation is too quick, the performance is degraded owing to the target signal. To overcome this problem, we propose an adaptive filter that suppresses the fluctuation of the ideal coefficients by utilizing a $rac{pi}{2}$ phase-delay device. This method assumes a frequency response that characterizes the transmission path from the interference source to the main input signal to be sufficiently smooth. In the numerical examples, the proposed method exhibits good performance in the presence of a frequency fluctuation when the forgetting factor is large. Moreover, we show that the proposed method reduces the calculation cost.
ER -