Title :
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
fDate :
10/1/1992 12:00:00 AM
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;
Journal_Title :
Signal Processing, IEEE Transactions on
