Independent component analysis by convex divergence minimization: Applications to brain fMRI analysis

Y. Matsuyama, S. Imahara

    研究成果: Conference contribution

    1 被引用数 (Scopus)

    抄録

    The f-ICA was derived from the minimization of the convex divergence. Software implementations showed remarkable speed as a gradient descent type. This was due to the effective use of past and/or future data.

    本文言語English
    ホスト出版物のタイトルProceedings of the International Joint Conference on Neural Networks
    ページ412-417
    ページ数6
    1
    出版ステータスPublished - 2001
    イベントInternational Joint Conference on Neural Networks (IJCNN'01) - Washington, DC
    継続期間: 2001 7 152001 7 19

    Other

    OtherInternational Joint Conference on Neural Networks (IJCNN'01)
    CityWashington, DC
    Period01/7/1501/7/19

    ASJC Scopus subject areas

    • Software

    フィンガープリント 「Independent component analysis by convex divergence minimization: Applications to brain fMRI analysis」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