Two-dimensional transform domain adaptive filters based on one-dimensional orthogonal transforms

M. N. Howard, R. A. Soni, William Kenneth Jenkins

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

    Abstract

    Recently it has been shown that two-dimensional (2-D) orthogonal transforms can be incorporated into 2-D FIR adaptive filters to improve the conditioning of the input auto correlation matrix eigenvalue spread, thereby improving the convergence rates for 2-D adaptive filters operating in colored noise. This paper considers two approaches to incorporating the transform. The first involves mapping the 2-D input data into a long 1-D vector, and then performing the orthogonalization with a 1-D sliding window orthogonal transform (the FFT is considered in this paper). The second approach performs the transform directly with a 2-D transform algorithm. Experiments demonstrate that similar reductions in eigenvalue spread result with both 1-D and 2-D transformations, both of which can greatly speed convergence in 2-D adaptive filters that have inherently slow convergence rates due to the large number of coefficients required in two dimensions.

    Original languageEnglish (US)
    Title of host publicationConference Record of the Asilomar Conference of Signals, Systems & Computers
    PublisherPubl by IEEE
    Pages1589-1593
    Number of pages5
    ISBN (Print)0818641207
    StatePublished - Dec 1 1993
    EventProceedings of the 27th Asilomar Conference on Signals, Systems & Computers - Pacific Grove, CA, USA
    Duration: Nov 1 1993Nov 3 1993

    Publication series

    NameConference Record of the Asilomar Conference of Signals, Systems & Computers
    Volume2
    ISSN (Print)1058-6393

    Other

    OtherProceedings of the 27th Asilomar Conference on Signals, Systems & Computers
    CityPacific Grove, CA, USA
    Period11/1/9311/3/93

    Fingerprint

    Adaptive filters
    FIR filters
    Autocorrelation
    Fast Fourier transforms
    Experiments

    All Science Journal Classification (ASJC) codes

    • Signal Processing
    • Computer Networks and Communications

    Cite this

    Howard, M. N., Soni, R. A., & Jenkins, W. K. (1993). Two-dimensional transform domain adaptive filters based on one-dimensional orthogonal transforms. In Conference Record of the Asilomar Conference of Signals, Systems & Computers (pp. 1589-1593). (Conference Record of the Asilomar Conference of Signals, Systems & Computers; Vol. 2). Publ by IEEE.
    Howard, M. N. ; Soni, R. A. ; Jenkins, William Kenneth. / Two-dimensional transform domain adaptive filters based on one-dimensional orthogonal transforms. Conference Record of the Asilomar Conference of Signals, Systems & Computers. Publ by IEEE, 1993. pp. 1589-1593 (Conference Record of the Asilomar Conference of Signals, Systems & Computers).
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    Howard, MN, Soni, RA & Jenkins, WK 1993, Two-dimensional transform domain adaptive filters based on one-dimensional orthogonal transforms. in Conference Record of the Asilomar Conference of Signals, Systems & Computers. Conference Record of the Asilomar Conference of Signals, Systems & Computers, vol. 2, Publ by IEEE, pp. 1589-1593, Proceedings of the 27th Asilomar Conference on Signals, Systems & Computers, Pacific Grove, CA, USA, 11/1/93.

    Two-dimensional transform domain adaptive filters based on one-dimensional orthogonal transforms. / Howard, M. N.; Soni, R. A.; Jenkins, William Kenneth.

    Conference Record of the Asilomar Conference of Signals, Systems & Computers. Publ by IEEE, 1993. p. 1589-1593 (Conference Record of the Asilomar Conference of Signals, Systems & Computers; Vol. 2).

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

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    Howard MN, Soni RA, Jenkins WK. Two-dimensional transform domain adaptive filters based on one-dimensional orthogonal transforms. In Conference Record of the Asilomar Conference of Signals, Systems & Computers. Publ by IEEE. 1993. p. 1589-1593. (Conference Record of the Asilomar Conference of Signals, Systems & Computers).