Adaptive multistage weighted order statistic filters based on the backpropagation algorithm

Author

Yin, Lin ; Astola, Jaakko ; Neuvo, Yrjo

Author_Institution

Dept. of Electr. Eng., Tampere Univ. of Technol., Finland

Volume

42

Issue

2

fYear

1994

fDate

2/1/1994 12:00:00 AM

Firstpage

419

Lastpage

422

Abstract

As a concise representation of stack filters, multistage weighted-order statistic (MWOS) filters are introduced, which correspond to multistage threshold logic gates or multilayer perceptrons in the binary domain. Two adaptive algorithms are derived for finding optimal MWOS filters under the mean absolute error criterion and the mean square error criterion, respectively. Experimental results from image enhancement are provided to compare the performance of adaptive MWOS filters and adaptive stack filters

Keywords

adaptive filters; backpropagation; binary sequences; digital filters; feedforward neural nets; image processing; least squares approximations; logic gates; threshold logic; adaptive multistage weighted order statistic filters; adaptive stack filters; backpropagation algorithm; image enhancement; multilayer perceptrons; multistage threshold logic gates; multistage weighted-order statistic filters; optimal MWOS filters; stack filters; Adaptive filters; Backpropagation algorithms; Boolean functions; Filtering algorithms; Logic gates; Multilayer perceptrons; Nonlinear filters; Signal processing algorithms; Statistics; Transversal filters;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.275617

Filename

275617