A reconsideration of improved PNLMS algorithm from metric combining viewpoint

Osamu Toda, Masahiro Yukawa

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    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.

    Original languageEnglish
    Title of host publicationConference Record of the 47th Asilomar Conference on Signals, Systems and Computers
    PublisherIEEE Computer Society
    Pages1951-1955
    Number of pages5
    ISBN (Print)9781479923908
    DOIs
    Publication statusPublished - 2013 Jan 1
    Event2013 47th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
    Duration: 2013 Nov 32013 Nov 6

    Publication series

    NameConference Record - Asilomar Conference on Signals, Systems and Computers
    ISSN (Print)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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  • Cite this

    Toda, O., & Yukawa, M. (2013). A reconsideration of improved PNLMS algorithm from metric combining viewpoint. In Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers (pp. 1951-1955). [6810645] (Conference Record - Asilomar Conference on Signals, Systems and Computers). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2013.6810645