A reconsideration of improved PNLMS algorithm from metric combining viewpoint

Osamu Toda, Masahiro Yukawa

    研究成果: Conference contribution

    1 被引用数 (Scopus)

    抄録

    In this paper, we show the importance of considering metric in adaptive filtering through a reconsideration of the improved proportionate normalized least mean square (IPNLMS) algorithm for sparse systems from a viewpoint of metric combining. IPNLMS convexly combines a positive-definite diagonal matrix (whose diagonal elements are proportional to the absolute values of the adaptive filter to reflect the system sparsity) with the identity matrix. We present the metric-combining NLMS (MC-NLMS) algorithm and derive, as its special example, the natural PNLMS (NPNLMS) algorithm. NPNLMS can be regarded as a modified version of IPNLMS and we show that NPNLMS is more natural (and performs better) than IPNLMS.

    本文言語English
    ホスト出版物のタイトルConference Record of the 47th Asilomar Conference on Signals, Systems and Computers
    出版社IEEE Computer Society
    ページ1951-1955
    ページ数5
    ISBN(印刷版)9781479923908
    DOI
    出版ステータスPublished - 2013 1 1
    イベント2013 47th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
    継続期間: 2013 11 32013 11 6

    出版物シリーズ

    名前Conference Record - Asilomar Conference on Signals, Systems and Computers
    ISSN(印刷版)1058-6393

    Other

    Other2013 47th Asilomar Conference on Signals, Systems and Computers
    CountryUnited States
    CityPacific Grove, CA
    Period13/11/313/11/6

    ASJC Scopus subject areas

    • Signal Processing
    • Computer Networks and Communications

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