Online learning based on iterative projections in sum space of linear and Gaussian reproducing kernel Hilbert spaces

    研究成果: Conference contribution

    1 被引用数 (Scopus)

    抄録

    We propose a novel multikernel adaptive filtering algorithm based on the iterative projections in the sum space of reproducing kernel Hilbert spaces. We employ linear and Gaussian kernels, envisioning an application to partially-linear-system identification/estimation. The algorithm is derived by reformulating the hyperplane projection along affine subspace (HYPASS) algorithm in the sum space. The projection is computable by virtue of Minh's theorem proved in 2010 as long as the input space has nonempty interior. 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ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ3362-3366
    ページ数5
    2015-August
    ISBN(印刷版)9781467369978
    DOI
    出版ステータスPublished - 2015 8 4
    イベント40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Brisbane, Australia
    継続期間: 2014 4 192014 4 24

    Other

    Other40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
    国/地域Australia
    CityBrisbane
    Period14/4/1914/4/24

    ASJC Scopus subject areas

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

    フィンガープリント

    「Online learning based on iterative projections in sum space of linear and Gaussian reproducing kernel Hilbert spaces」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