On adaptivity of online model selection method based on multikernel adaptive filtering

Masahiro Yukawa, Ryu Ichiro Ishii

    研究成果: Conference contribution

    4 被引用数 (Scopus)

    抄録

    We investigate adaptivity of the online model selection method which has been proposed recently within the multikernel adaptive filtering framework. Specifically, we consider a situation in which the nonlinear system under study changes during adaptation and an appropriate kernel also does accordingly. Our time-varying cost functions involve three regularizers: the ℓ1 norm and two block ℓ1 norms which promote sparsity both in the kernel and data groups. The block ℓ1 regularizers are approximated by their Moreau envelopes, and the adaptive proximal forward-backward splitting (APFBS) method is applied to the approximated cost function. Numerical examples show that the proposed algorithm can adaptively estimate a reasonable model.

    本文言語English
    ホスト出版物のタイトル2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013
    DOI
    出版ステータスPublished - 2013 12月 1
    イベント2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013 - Kaohsiung, Taiwan, Province of China
    継続期間: 2013 10月 292013 11月 1

    出版物シリーズ

    名前2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013

    Other

    Other2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013
    国/地域Taiwan, Province of China
    CityKaohsiung
    Period13/10/2913/11/1

    ASJC Scopus subject areas

    • 情報システム
    • 信号処理

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