Title :
Theory of order statistic filters and their relationship to linear FIR filters
Author :
Longbotham, Harold Gene ; Bovik, Alan Conrad
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas Univ., Austin, TX, USA
fDate :
2/1/1989 12:00:00 AM
Abstract :
Necessary and/or sufficient conditions on both the filter coefficients and the signal process are derived in order that nonrecursive order statistic (OS) and linear filtering are equivalent operations. The results indicate that an understanding of OS filters hinges on a better understanding of the properties of signals containing logically monotonic components. The results extend a number of previous theories characterizing the well-known median and ranked-order filters to a broader class of filters and input signals
Keywords :
filtering and prediction theory; statistics; coefficients; input signals; linear FIR filters; linear filtering; logically monotonic components; nonrecursive order statistic; order statistic filters; signal processing; Digital filters; Ear; Filtering theory; Finite impulse response filter; Maximum likelihood detection; Nonlinear filters; Signal processing; Signal processing algorithms; Smoothing methods; Statistics;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on