An efficient parallel variable-metric projection algorithm based on set-theoretic and Krylov-proportionate adaptive filtering techniques

Masahiro Yukawa, Isao Yamada

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

Abstract

We blend two adaptive filtering techniques for further efficiency: the set-theoretic adaptive filter (STAF, Yamada et al. 2002) and the Krylov-proportionate adaptive filter (KPAF, Yukawa 2009). Although the ideas behind these techniques are quite different from each other, there is a way to blend them together by noticing that KPAF can be seen as a sort of 'variable-metric' projection algorithm. We propose a blended algorithm named set-theoretic Krylov-proportionate adaptive filter (SKAF), which features iterative parallel variable-metric projection onto well-designed closed convex sets. We present comparisons in complexity and mean square error (MSE) performance, showing significant advantages of the proposed algorithm over the existing algorithms.

Original languageEnglish
Title of host publicationAPSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference
Pages418-421
Number of pages4
Publication statusPublished - 2009
Externally publishedYes
EventAsia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009 - Sapporo, Japan
Duration: 2009 Oct 42009 Oct 7

Other

OtherAsia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009
CountryJapan
CitySapporo
Period09/10/409/10/7

Fingerprint

Adaptive filtering
projection
Adaptive filters
Mean square error
efficiency
performance

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Electrical and Electronic Engineering
  • Communication

Cite this

Yukawa, M., & Yamada, I. (2009). An efficient parallel variable-metric projection algorithm based on set-theoretic and Krylov-proportionate adaptive filtering techniques. In APSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference (pp. 418-421)

An efficient parallel variable-metric projection algorithm based on set-theoretic and Krylov-proportionate adaptive filtering techniques. / Yukawa, Masahiro; Yamada, Isao.

APSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference. 2009. p. 418-421.

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

Yukawa, M & Yamada, I 2009, An efficient parallel variable-metric projection algorithm based on set-theoretic and Krylov-proportionate adaptive filtering techniques. in APSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference. pp. 418-421, Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009, Sapporo, Japan, 09/10/4.
Yukawa M, Yamada I. An efficient parallel variable-metric projection algorithm based on set-theoretic and Krylov-proportionate adaptive filtering techniques. In APSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference. 2009. p. 418-421
Yukawa, Masahiro ; Yamada, Isao. / An efficient parallel variable-metric projection algorithm based on set-theoretic and Krylov-proportionate adaptive filtering techniques. APSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference. 2009. pp. 418-421
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