Optimizing the performance of polynomial adaptive filters

making quadratic filters converge like linear filters

Charles W. Therrien, William Kenneth Jenkins, Xiaohui Li

    Research output: Contribution to journalArticle

    4 Citations (Scopus)

    Abstract

    The correlation properties of the input vector determine the rate of convergence of the LMS algorithm for Volterra adaptive filters and are optimal when the nonlinear input terms are uncorrelated. This correspondence presents new results on the correlation properties for second-order Volterra filters and shows that when the input signal is whitened, the nonlinear terms automatically become uncorrelated.

    Original languageEnglish (US)
    Pages (from-to)1169-1171
    Number of pages3
    JournalIEEE Transactions on Signal Processing
    Volume47
    Issue number4
    DOIs
    StatePublished - Apr 1 1999

    Fingerprint

    Adaptive filters
    Polynomials

    All Science Journal Classification (ASJC) codes

    • Signal Processing
    • Electrical and Electronic Engineering

    Cite this

    Therrien, Charles W. ; Jenkins, William Kenneth ; Li, Xiaohui. / Optimizing the performance of polynomial adaptive filters : making quadratic filters converge like linear filters. In: IEEE Transactions on Signal Processing. 1999 ; Vol. 47, No. 4. pp. 1169-1171.
    @article{42e5129cc3cd41d8b4ccd21b2feb119f,
    title = "Optimizing the performance of polynomial adaptive filters: making quadratic filters converge like linear filters",
    abstract = "The correlation properties of the input vector determine the rate of convergence of the LMS algorithm for Volterra adaptive filters and are optimal when the nonlinear input terms are uncorrelated. This correspondence presents new results on the correlation properties for second-order Volterra filters and shows that when the input signal is whitened, the nonlinear terms automatically become uncorrelated.",
    author = "Therrien, {Charles W.} and Jenkins, {William Kenneth} and Xiaohui Li",
    year = "1999",
    month = "4",
    day = "1",
    doi = "10.1109/78.752619",
    language = "English (US)",
    volume = "47",
    pages = "1169--1171",
    journal = "IEEE Transactions on Signal Processing",
    issn = "1053-587X",
    publisher = "Institute of Electrical and Electronics Engineers Inc.",
    number = "4",

    }

    Optimizing the performance of polynomial adaptive filters : making quadratic filters converge like linear filters. / Therrien, Charles W.; Jenkins, William Kenneth; Li, Xiaohui.

    In: IEEE Transactions on Signal Processing, Vol. 47, No. 4, 01.04.1999, p. 1169-1171.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Optimizing the performance of polynomial adaptive filters

    T2 - making quadratic filters converge like linear filters

    AU - Therrien, Charles W.

    AU - Jenkins, William Kenneth

    AU - Li, Xiaohui

    PY - 1999/4/1

    Y1 - 1999/4/1

    N2 - The correlation properties of the input vector determine the rate of convergence of the LMS algorithm for Volterra adaptive filters and are optimal when the nonlinear input terms are uncorrelated. This correspondence presents new results on the correlation properties for second-order Volterra filters and shows that when the input signal is whitened, the nonlinear terms automatically become uncorrelated.

    AB - The correlation properties of the input vector determine the rate of convergence of the LMS algorithm for Volterra adaptive filters and are optimal when the nonlinear input terms are uncorrelated. This correspondence presents new results on the correlation properties for second-order Volterra filters and shows that when the input signal is whitened, the nonlinear terms automatically become uncorrelated.

    UR - http://www.scopus.com/inward/record.url?scp=0033116464&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=0033116464&partnerID=8YFLogxK

    U2 - 10.1109/78.752619

    DO - 10.1109/78.752619

    M3 - Article

    VL - 47

    SP - 1169

    EP - 1171

    JO - IEEE Transactions on Signal Processing

    JF - IEEE Transactions on Signal Processing

    SN - 1053-587X

    IS - 4

    ER -