Position-based competition learning of neural-networks array

R. Saegusa, P. Hartono, S. Hashimoto

    研究成果: Conference contribution

    抜粋

    In this paper, we propose a model of neural-network array composed of a number of MLPs (members), in which each member can be automatically trained to recognize the different dynamics of time series data. The proposed array adopts a position-based competitive learning methods that puts members with similar dynamics close to each other. The proposed array model intends to deal effectively with switching dynamics problems and produce a map of the dynamics.

    元の言語English
    ホスト出版物のタイトルProceedings of the International Joint Conference on Neural Networks
    ページ2817-2820
    ページ数4
    4
    出版物ステータス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)
    Washington, DC
    期間01/7/1501/7/19

      フィンガープリント

    ASJC Scopus subject areas

    • Software

    これを引用

    Saegusa, R., Hartono, P., & Hashimoto, S. (2001). Position-based competition learning of neural-networks array. : Proceedings of the International Joint Conference on Neural Networks (巻 4, pp. 2817-2820)