A new lattice-based adaptive notch filtering algorithm with improved mean update term

Shinichiro Nakamura, Shunsuke Koshita, Masahide Abe, Masayuki Kawamata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we propose a new lattice-based adaptive notch filtering algorithm which has faster convergence characteristics than Regalia's Simplified Lattice Algorithm (SLA). Our algorithm makes use of the weighted sum of SLA and the Lattice Gradient Algorithm. We prove that the mean update term of our algorithm is larger than that of SLA when the input signal consists of a single sinusoid and a background white noise. Furthermore, our algorithm does not change the local convergence characteristics near the sinusoidal frequency. Consequently, the proposed algorithm achieves faster convergence than SLA. A simulation result shows that the proposed algorithm finds the sinusoidal frequency faster than SLA.

Original languageEnglish
Title of host publication2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013
DOIs
Publication statusPublished - 2013
Event2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013 - Kaohsiung, Taiwan, Province of China
Duration: 2013 Oct 292013 Nov 1

Publication series

Name2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013

Other

Other2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013
CountryTaiwan, Province of China
CityKaohsiung
Period13/10/2913/11/1

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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