A stochastic behavior analysis of stochastic restricted-gradient descent algorithm in reproducing kernel hilbert spaces

Masa Aki Takizawa, Masahiro Yukawa, Cedric Richard

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

    4 Citations (Scopus)

    Abstract

    This paper presents a stochastic behavior analysis of a kernel-based stochastic restricted-gradient descent method. The restricted gradient gives a steepest ascent direction within the so-called dictionary subspace. The analysis provides the transient and steady state performance in the mean squared error criterion. It also includes stability conditions in the mean and mean-square sense. The present study is based on the analysis of the kernel normalized least mean square (KNLMS) algorithm initially proposed by Chen et al. Simulation results validate the analysis.

    Original languageEnglish
    Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages2001-2005
    Number of pages5
    Volume2015-August
    ISBN (Print)9781467369978
    DOIs
    Publication statusPublished - 2015 Aug 4
    Event40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Brisbane, Australia
    Duration: 2014 Apr 192014 Apr 24

    Other

    Other40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
    CountryAustralia
    CityBrisbane
    Period14/4/1914/4/24

    Keywords

    • kernel adaptive filter
    • performance analysis
    • reproducing kernel Hilbert space
    • the KLMS algorithm

    ASJC Scopus subject areas

    • Signal Processing
    • Software
    • Electrical and Electronic Engineering

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  • Cite this

    Takizawa, M. A., Yukawa, M., & Richard, C. (2015). A stochastic behavior analysis of stochastic restricted-gradient descent algorithm in reproducing kernel hilbert spaces. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (Vol. 2015-August, pp. 2001-2005). [7178321] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2015.7178321