Krylov-proportionate NLMS algorithm based on multistage Wiener filter representation

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

4 Citations (Scopus)

Abstract

This paper proposes a fast converging adaptive filtering algorithm named Krylov-proportionate normalized least mean-square (KPNLMS) by extending the proportionate normalized least mean square (PNLMS) algorithm. PNLMS is known to exhibit faster convergence than the standard NLMS algorithm for sparse unknown systems. The proposed algorithm attains similar effects for non-sparse unknown systems by constructing, based on the multistage Wiener filter (MWF) representation, an orthonormal basis with which the unknown system has a sparse structure. The proposed algorithm can be analyzed by the adaptive parallel variable-metric projection framework. Numerical studies for non-sparse unknown systems are presented, comparing KPNLMS and the MWF-based reduced-rank method.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages3801-3804
Number of pages4
DOIs
Publication statusPublished - 2008 Sep 16
Externally publishedYes
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: 2008 Mar 312008 Apr 4

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
CountryUnited States
CityLas Vegas, NV
Period08/3/3108/4/4

Keywords

  • Adaptive filters
  • Multistage wiener filter
  • Proportionate NLMS

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Yukawa, M. (2008). Krylov-proportionate NLMS algorithm based on multistage Wiener filter representation. In 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP (pp. 3801-3804). [4518481] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2008.4518481