A parallel notch filter (PNF) for eliminating a sinusoidal signal whose frequency and phase are unknown, has been proposed previously. The PNF achieves both fast convergence and high estimation accuracy when the step-size for adaptation is appropriately determined. However, there has been no discussion of how to determine the appropriate step-size. In this paper, we derive the convergence condition on the step-size, and propose an adaptive algorithm with variable step-size so that convergence of the PNF is automatically satisfied. Moreover, we present a new filtering structure of the PNF that increases the convergence speed while keeping the estimation accuracy. We also derive a variable step-size scheme for the new PNF to guarantee the convergence. Simulation results show the effectiveness of the proposed method.
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Arata KAWAMURA, Youji IIGUNI, Yoshio ITOH, "An Adaptive Algorithm with Variable Step-Size for Parallel Notch Filter" in IEICE TRANSACTIONS on Fundamentals,
vol. E89-A, no. 2, pp. 511-519, February 2006, doi: 10.1093/ietfec/e89-a.2.511.
Abstract: A parallel notch filter (PNF) for eliminating a sinusoidal signal whose frequency and phase are unknown, has been proposed previously. The PNF achieves both fast convergence and high estimation accuracy when the step-size for adaptation is appropriately determined. However, there has been no discussion of how to determine the appropriate step-size. In this paper, we derive the convergence condition on the step-size, and propose an adaptive algorithm with variable step-size so that convergence of the PNF is automatically satisfied. Moreover, we present a new filtering structure of the PNF that increases the convergence speed while keeping the estimation accuracy. We also derive a variable step-size scheme for the new PNF to guarantee the convergence. Simulation results show the effectiveness of the proposed method.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e89-a.2.511/_p
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@ARTICLE{e89-a_2_511,
author={Arata KAWAMURA, Youji IIGUNI, Yoshio ITOH, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Adaptive Algorithm with Variable Step-Size for Parallel Notch Filter},
year={2006},
volume={E89-A},
number={2},
pages={511-519},
abstract={A parallel notch filter (PNF) for eliminating a sinusoidal signal whose frequency and phase are unknown, has been proposed previously. The PNF achieves both fast convergence and high estimation accuracy when the step-size for adaptation is appropriately determined. However, there has been no discussion of how to determine the appropriate step-size. In this paper, we derive the convergence condition on the step-size, and propose an adaptive algorithm with variable step-size so that convergence of the PNF is automatically satisfied. Moreover, we present a new filtering structure of the PNF that increases the convergence speed while keeping the estimation accuracy. We also derive a variable step-size scheme for the new PNF to guarantee the convergence. Simulation results show the effectiveness of the proposed method.},
keywords={},
doi={10.1093/ietfec/e89-a.2.511},
ISSN={1745-1337},
month={February},}
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TY - JOUR
TI - An Adaptive Algorithm with Variable Step-Size for Parallel Notch Filter
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 511
EP - 519
AU - Arata KAWAMURA
AU - Youji IIGUNI
AU - Yoshio ITOH
PY - 2006
DO - 10.1093/ietfec/e89-a.2.511
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E89-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2006
AB - A parallel notch filter (PNF) for eliminating a sinusoidal signal whose frequency and phase are unknown, has been proposed previously. The PNF achieves both fast convergence and high estimation accuracy when the step-size for adaptation is appropriately determined. However, there has been no discussion of how to determine the appropriate step-size. In this paper, we derive the convergence condition on the step-size, and propose an adaptive algorithm with variable step-size so that convergence of the PNF is automatically satisfied. Moreover, we present a new filtering structure of the PNF that increases the convergence speed while keeping the estimation accuracy. We also derive a variable step-size scheme for the new PNF to guarantee the convergence. Simulation results show the effectiveness of the proposed method.
ER -