Set-theoretic reduced-rank adaptive filtering by adaptive projected subgradient method

Masahiro Yukawa, Rodrigo C. De Lamare, Isao Yamada

研究成果: Conference contribution

抄録

In this paper, we propose a novel reduced-rank adaptive filtering algorithm based on set-theoretic adaptive filtering. We discuss the orthonormality of the transformation (rank-reduction) matrix. We present, under the assumption that the transformation matrix has an orthonormal structure, an interpretation of the proposed algorithm in the original (fullsize) vector space. The interpretation suggests that the use of an orthonormal transformation matrix leads to performance depending solely on the subspace spanned by the column vectors of the matrix but not on the matrix itself. This is verified by simulations, and the numerical examples demonstrate the efficacy of the proposed algorithm.

本文言語English
ホスト出版物のタイトルConference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC
ページ422-426
ページ数5
DOI
出版ステータスPublished - 2007 12 1
外部発表はい
イベント41st Asilomar Conference on Signals, Systems and Computers, ACSSC - Pacific Grove, CA, United States
継続期間: 2007 11 42007 11 7

出版物シリーズ

名前Conference Record - Asilomar Conference on Signals, Systems and Computers
ISSN(印刷版)1058-6393

Other

Other41st Asilomar Conference on Signals, Systems and Computers, ACSSC
CountryUnited States
CityPacific Grove, CA
Period07/11/407/11/7

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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