Two-dimensional transform domain adaptive filtering

M. N. Howard, William Kenneth Jenkins

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

    1 Scopus citations

    Abstract

    A two-dimensional (2-D) orthogonal transform is incorporated into a 2-D FIR adaptive filter to improve the input autocorrelation matrix eigenvalue spread, thereby achieving improved convergence rates for 2-D adaptive filters operating in colored noise. Eigenvalues analyses are used to predict the relative merits of different transforms when operating on different colored noise inputs. Both theoretical predictions and experimental results are presented to demonstrate that the reduction in eigenvalue spread results in greatly improved convergence rates in 2-D adaptive filters, which suffer from inherently slow convergence due to the large number of coefficients required in two dimensions.

    Original languageEnglish (US)
    Title of host publicationMidwest Symposium on Circuits and Systems
    PublisherPubl by IEEE
    Pages121-124
    Number of pages4
    ISBN (Print)0780317610
    StatePublished - Dec 1 1993
    EventProceedings of the 36th Midwest Symposium on Circuits and Systems - Detroit, MI, USA
    Duration: Aug 16 1993Aug 18 1993

    Publication series

    NameMidwest Symposium on Circuits and Systems
    Volume1

    Other

    OtherProceedings of the 36th Midwest Symposium on Circuits and Systems
    CityDetroit, MI, USA
    Period8/16/938/18/93

    All Science Journal Classification (ASJC) codes

    • Electronic, Optical and Magnetic Materials
    • Electrical and Electronic Engineering

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  • Cite this

    Howard, M. N., & Jenkins, W. K. (1993). Two-dimensional transform domain adaptive filtering. In Midwest Symposium on Circuits and Systems (pp. 121-124). (Midwest Symposium on Circuits and Systems; Vol. 1). Publ by IEEE.