Correct Formulation of Gradient Characteristics for Adaptive Notch Filters Based on Monotonically Increasing Gradient Algorithm
Summary :
In the field of adaptive notch filtering, Monotonically Increasing Gradient (MIG) algorithm has recently been proposed by Sugiura and Shimamura [1], where it is claimed that the MIG algorithm shows monotonically increasing gradient characteristics. However, our analysis has found that the underlying theory in [1] includes crucial errors. This letter shows that the formulation of the gradient characteristics in [1] is incorrect, and reveals that the MIG algorithm fails to realize monotonically increasing gradient characteristics when the input signal includes white noise.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.7 pp.1557-1561
- Publication Date
- 2017/07/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E100.A.1557
- Type of Manuscript
- LETTER
- Category
- Digital Signal Processing
Authors
Shunsuke KOSHITA
Tohoku University
Hiroyuki MUNAKATA
Tohoku University
Masahide ABE
Tohoku University
Masayuki KAWAMATA
Tohoku University
Keyword
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Shunsuke KOSHITA, Hiroyuki MUNAKATA, Masahide ABE, Masayuki KAWAMATA, "Correct Formulation of Gradient Characteristics for Adaptive Notch Filters Based on Monotonically Increasing Gradient Algorithm" in IEICE TRANSACTIONS on Fundamentals,
vol. E100-A, no. 7, pp. 1557-1561, July 2017, doi: 10.1587/transfun.E100.A.1557.
Abstract: In the field of adaptive notch filtering, Monotonically Increasing Gradient (MIG) algorithm has recently been proposed by Sugiura and Shimamura [1], where it is claimed that the MIG algorithm shows monotonically increasing gradient characteristics. However, our analysis has found that the underlying theory in [1] includes crucial errors. This letter shows that the formulation of the gradient characteristics in [1] is incorrect, and reveals that the MIG algorithm fails to realize monotonically increasing gradient characteristics when the input signal includes white noise.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E100.A.1557/_p
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@ARTICLE{e100-a_7_1557,
author={Shunsuke KOSHITA, Hiroyuki MUNAKATA, Masahide ABE, Masayuki KAWAMATA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Correct Formulation of Gradient Characteristics for Adaptive Notch Filters Based on Monotonically Increasing Gradient Algorithm},
year={2017},
volume={E100-A},
number={7},
pages={1557-1561},
abstract={In the field of adaptive notch filtering, Monotonically Increasing Gradient (MIG) algorithm has recently been proposed by Sugiura and Shimamura [1], where it is claimed that the MIG algorithm shows monotonically increasing gradient characteristics. However, our analysis has found that the underlying theory in [1] includes crucial errors. This letter shows that the formulation of the gradient characteristics in [1] is incorrect, and reveals that the MIG algorithm fails to realize monotonically increasing gradient characteristics when the input signal includes white noise.},
keywords={},
doi={10.1587/transfun.E100.A.1557},
ISSN={1745-1337},
month={July},}
Copy
TY - JOUR
TI - Correct Formulation of Gradient Characteristics for Adaptive Notch Filters Based on Monotonically Increasing Gradient Algorithm
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1557
EP - 1561
AU - Shunsuke KOSHITA
AU - Hiroyuki MUNAKATA
AU - Masahide ABE
AU - Masayuki KAWAMATA
PY - 2017
DO - 10.1587/transfun.E100.A.1557
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E100-A
IS - 7
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - July 2017
AB - In the field of adaptive notch filtering, Monotonically Increasing Gradient (MIG) algorithm has recently been proposed by Sugiura and Shimamura [1], where it is claimed that the MIG algorithm shows monotonically increasing gradient characteristics. However, our analysis has found that the underlying theory in [1] includes crucial errors. This letter shows that the formulation of the gradient characteristics in [1] is incorrect, and reveals that the MIG algorithm fails to realize monotonically increasing gradient characteristics when the input signal includes white noise.
ER -
English
