A new adaptive notch filtering Algorithm based on normalized Lattice structure with improved mean update term

Shinichiro Nakamura, Shunsuke Koshita, Masahide Abe, Masayuki Kawamata

Research output: Contribution to journalArticle

5 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1482-1493
Number of pages12
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE98A
Issue number7
DOIs
Publication statusPublished - 2015 Jul 1

Keywords

  • Adaptive notch filter
  • Affine Combination
  • Mean update term
  • Normalized lattice structure
  • Simplified Lattice Algorithm

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics

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