Title :
Parametric analysis of weighted order statistics filters
Author :
Yang, Ruikang ; Gabbouj, Moncef ; Yu, Pao-Ta
Author_Institution :
Audio-Visual Process. Lab., Nokia Res. Center, Tampere, Finland
fDate :
6/1/1994 12:00:00 AM
Abstract :
The authors study the convergence properties of weighted order statistics filters. Based on a set of parameters, weighted order statistics filters are divided into five categories making their convergence properties easily understood. They show that any symmetric weighted order statistics filters will make the input sequence converge to a root or oscillate in a cycle of period 2. This result is significant since a restriction imposed by an earlier research is eliminated making the result applicable for the whole class of symmetric weighted order statistics filters. A condition to guarantee convergence of symmetric weighted order statistics filters is also derived.<>
Keywords :
convergence of numerical methods; digital filters; filtering and prediction theory; network parameters; statistics; convergence properties; input sequence; parametric analysis; symmetric weighted order filters; weighted order statistics filters; Attenuation; Convergence; Filtering; Filters; Image processing; Laboratories; Logic functions; Parametric statistics; Statistical analysis; Statistical distributions;
Journal_Title :
Signal Processing Letters, IEEE
