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

Volume

1

Issue

6

fYear

1994

fDate

6/1/1994 12:00:00 AM

Firstpage

95

Lastpage

98

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;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/97.295344

Filename

295344