An efficient sparse kernel adaptive filtering algorithm based on isomorphism between functional subspace and Euclidean space

Masa Aki Takizawa, Masahiro Yukawa

    研究成果: Conference contribution

    8 被引用数 (Scopus)

    抄録

    The existing kernel filtering algorithms are classified into two categories depending on what space the optimization is formulated in. This paper bridges the two different approaches by focusing on the isomorphism between the dictionary subspace and a Euclidean space with the inner product defined by the kernel matrix. Based on the isomorphism, we propose a novel kernel adaptive filtering algorithm which adaptively refines the dictionary and thereby achieves excellent performance with a small dictionary size. Numerical examples show the efficacy of the proposed algorithm.

    本文言語English
    ホスト出版物のタイトル2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ4508-4512
    ページ数5
    ISBN(印刷版)9781479928927
    DOI
    出版ステータスPublished - 2014 1 1
    イベント2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy
    継続期間: 2014 5 42014 5 9

    出版物シリーズ

    名前ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    ISSN(印刷版)1520-6149

    Other

    Other2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
    国/地域Italy
    CityFlorence
    Period14/5/414/5/9

    ASJC Scopus subject areas

    • ソフトウェア
    • 信号処理
    • 電子工学および電気工学

    フィンガープリント

    「An efficient sparse kernel adaptive filtering algorithm based on isomorphism between functional subspace and Euclidean space」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

    引用スタイル