On signal recovery with adaptive order statistic filters

Author

Williamson, Geoffrey A. ; Clarkson, Peter M.

Author_Institution

Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA

Volume

40

Issue

10

fYear

1992

fDate

10/1/1992 12:00:00 AM

Firstpage

2622

Lastpage

2626

Abstract

Adaptive order statistic filters are used to estimate a constant amplitude signal embedded in noise with unknown statistics. Iterative algorithms are proposed which adapt the order statistic filter to minimize the mean-square estimation error, both with and without an unbiasedness constraint. For each case, the algorithm used is shown to achieve convergence in the mean to the optimal filter. Properties of the convergence rates are discussed, and conditions for convergence in mean square are noted

Keywords

adaptive filters; convergence of numerical methods; digital filters; iterative methods; signal processing; adaptive order statistic filters; constant amplitude signal; convergence rates; iterative algorithms; mean-square estimation error; noise; optimal filter; signal recovery; unknown statistics; Adaptive filters; Adaptive signal processing; Convergence; Frequency; H infinity control; Signal processing algorithms; Signal resolution; Spatial resolution; Speech processing; Statistics;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.157309

Filename

157309