Mean-square error surfaces of 2-D recursive adaptive filters

Jeffrey C. Strait, William Kenneth Jenkins

    Research output: Contribution to conferencePaper

    Abstract

    Recursive adaptive filters which utilize a stochastic gradient search algorithm in order to optimize their coefficients are apt to converge to local minima if the meansquare error surface is not unimodal. Such conditions are known to result since the IIR mean-square error surface is not quadratic. Two-dimensional adaptive filter error surfaces are examined in this paper, and their properties are seen to be very similar to those of 1-D IIR adaptive filter error surfaces.

    Original languageEnglish (US)
    Pages797-800
    Number of pages4
    StatePublished - Dec 1 1994
    EventProceedings of the 37th Midwest Symposium on Circuits and Systems. Part 2 (of 2) - Lafayette, LA, USA
    Duration: Aug 3 1994Aug 5 1994

    Other

    OtherProceedings of the 37th Midwest Symposium on Circuits and Systems. Part 2 (of 2)
    CityLafayette, LA, USA
    Period8/3/948/5/94

    All Science Journal Classification (ASJC) codes

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

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  • Cite this

    Strait, J. C., & Jenkins, W. K. (1994). Mean-square error surfaces of 2-D recursive adaptive filters. 797-800. Paper presented at Proceedings of the 37th Midwest Symposium on Circuits and Systems. Part 2 (of 2), Lafayette, LA, USA, .