抄録
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.
本文言語 | English |
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ページ | 418-421 |
ページ数 | 4 |
出版ステータス | Published - 2009 12月 1 |
外部発表 | はい |
イベント | Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009 - Sapporo, Japan 継続期間: 2009 10月 4 → 2009 10月 7 |
Other
Other | Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009 |
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国/地域 | Japan |
City | Sapporo |
Period | 09/10/4 → 09/10/7 |
ASJC Scopus subject areas
- コンピュータ ネットワークおよび通信
- 情報システム
- 電子工学および電気工学
- 通信