A New Adaptive Notch Filtering Algorithm Based on Normalized Lattice Structure with Improved Mean Update Term

Shinichiro NAKAMURA; Shunsuke KOSHITA; Masahide ABE; Masayuki KAWAMATA

doi:10.1587/transfun.E98.A.1482

A New Adaptive Notch Filtering Algorithm Based on Normalized Lattice Structure with Improved Mean Update Term

Shinichiro NAKAMURA, Shunsuke KOSHITA, Masahide ABE, Masayuki KAWAMATA

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In this paper, we propose Affine Combination Lattice Algorithm (ACLA) as a new lattice-based adaptive notch filtering algorithm. The ACLA makes use of the affine combination of Regalia's Simplified Lattice Algorithm (SLA) and Lattice Gradient Algorithm (LGA). It is proved that the ACLA has faster convergence speed than the conventional lattice-based algorithms. We conduct this proof by means of theoretical analysis of the mean update term. Specifically, we show that the mean update term of the ACLA is always larger than that of the conventional algorithms. Simulation examples demonstrate the validity of this analytical result and the utility of the ACLA. In addition, we also derive the step-size bound for the ACLA. Furthermore, we show that this step-size bound is characterized by the gradient of the mean update term.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E98-A No.7 pp.1482-1493

Publication Date: 2015/07/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E98.A.1482

Type of Manuscript: PAPER

Category: Digital Signal Processing

Authors

Shinichiro NAKAMURA
  Tohoku University
Shunsuke KOSHITA
  Tohoku University
Masahide ABE
  Tohoku University
Masayuki KAWAMATA
  Tohoku University

Keyword

adaptive notch filter, affine combination, mean update term, normalized lattice structure, simplified lattice algorithm

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Shinichiro NAKAMURA, Shunsuke KOSHITA, Masahide ABE, Masayuki KAWAMATA, "A New Adaptive Notch Filtering Algorithm Based on Normalized Lattice Structure with Improved Mean Update Term" in IEICE TRANSACTIONS on Fundamentals, vol. E98-A, no. 7, pp. 1482-1493, July 2015, doi: 10.1587/transfun.E98.A.1482.
Abstract: In this paper, we propose Affine Combination Lattice Algorithm (ACLA) as a new lattice-based adaptive notch filtering algorithm. The ACLA makes use of the affine combination of Regalia's Simplified Lattice Algorithm (SLA) and Lattice Gradient Algorithm (LGA). It is proved that the ACLA has faster convergence speed than the conventional lattice-based algorithms. We conduct this proof by means of theoretical analysis of the mean update term. Specifically, we show that the mean update term of the ACLA is always larger than that of the conventional algorithms. Simulation examples demonstrate the validity of this analytical result and the utility of the ACLA. In addition, we also derive the step-size bound for the ACLA. Furthermore, we show that this step-size bound is characterized by the gradient of the mean update term.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/transfun.E98.A.1482/_p

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@ARTICLE{e98-a_7_1482,
author={Shinichiro NAKAMURA, Shunsuke KOSHITA, Masahide ABE, Masayuki KAWAMATA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A New Adaptive Notch Filtering Algorithm Based on Normalized Lattice Structure with Improved Mean Update Term},
year={2015},
volume={E98-A},
number={7},
pages={1482-1493},
abstract={In this paper, we propose Affine Combination Lattice Algorithm (ACLA) as a new lattice-based adaptive notch filtering algorithm. The ACLA makes use of the affine combination of Regalia's Simplified Lattice Algorithm (SLA) and Lattice Gradient Algorithm (LGA). It is proved that the ACLA has faster convergence speed than the conventional lattice-based algorithms. We conduct this proof by means of theoretical analysis of the mean update term. Specifically, we show that the mean update term of the ACLA is always larger than that of the conventional algorithms. Simulation examples demonstrate the validity of this analytical result and the utility of the ACLA. In addition, we also derive the step-size bound for the ACLA. Furthermore, we show that this step-size bound is characterized by the gradient of the mean update term.},
keywords={},
doi={10.1587/transfun.E98.A.1482},
ISSN={1745-1337},
month={July},}

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TY - JOUR
TI - A New Adaptive Notch Filtering Algorithm Based on Normalized Lattice Structure with Improved Mean Update Term
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1482
EP - 1493
AU - Shinichiro NAKAMURA
AU - Shunsuke KOSHITA
AU - Masahide ABE
AU - Masayuki KAWAMATA
PY - 2015
DO - 10.1587/transfun.E98.A.1482
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E98-A
IS - 7
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - July 2015
AB - In this paper, we propose Affine Combination Lattice Algorithm (ACLA) as a new lattice-based adaptive notch filtering algorithm. The ACLA makes use of the affine combination of Regalia's Simplified Lattice Algorithm (SLA) and Lattice Gradient Algorithm (LGA). It is proved that the ACLA has faster convergence speed than the conventional lattice-based algorithms. We conduct this proof by means of theoretical analysis of the mean update term. Specifically, we show that the mean update term of the ACLA is always larger than that of the conventional algorithms. Simulation examples demonstrate the validity of this analytical result and the utility of the ACLA. In addition, we also derive the step-size bound for the ACLA. Furthermore, we show that this step-size bound is characterized by the gradient of the mean update term.
ER -