Projection algorithms for two-dimensional adaptive filtering applications

Robert A. Soni, W. Kenneth Jenkins

    Research output: Contribution to journalConference article

    6 Citations (Scopus)

    Abstract

    In this paper, we present a family of `new' two-dimensional adaptive filtering algorithms for image processing applications. These algorithms are multi-dimensional versions of the families of data-reusing and projection algorithms. These two classes of algorithms allow the adaptive filtering system designer to choose performance and computational complexity by changing parameters without actually changing algorithm structure. By changing parameters, the desired convergence rate can be achieved at the expense of additional computational complexity. Experiments show that significant improvement may be obtained by marginal increases in computational complexity over the traditional normalized LMS algorithm.

    Original languageEnglish (US)
    Pages (from-to)333-337
    Number of pages5
    JournalConference Record of the Asilomar Conference on Signals, Systems and Computers
    Volume1
    StatePublished - Jan 1 1998
    EventProceedings of the 1997 31st Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2) - Pacific Grove, CA, USA
    Duration: Nov 2 1997Nov 5 1997

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    Adaptive filtering
    Computational complexity
    Image processing
    Experiments

    All Science Journal Classification (ASJC) codes

    • Signal Processing
    • Computer Networks and Communications

    Cite this

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    title = "Projection algorithms for two-dimensional adaptive filtering applications",
    abstract = "In this paper, we present a family of `new' two-dimensional adaptive filtering algorithms for image processing applications. These algorithms are multi-dimensional versions of the families of data-reusing and projection algorithms. These two classes of algorithms allow the adaptive filtering system designer to choose performance and computational complexity by changing parameters without actually changing algorithm structure. By changing parameters, the desired convergence rate can be achieved at the expense of additional computational complexity. Experiments show that significant improvement may be obtained by marginal increases in computational complexity over the traditional normalized LMS algorithm.",
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    Projection algorithms for two-dimensional adaptive filtering applications. / Soni, Robert A.; Jenkins, W. Kenneth.

    In: Conference Record of the Asilomar Conference on Signals, Systems and Computers, Vol. 1, 01.01.1998, p. 333-337.

    Research output: Contribution to journalConference article

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