DocumentCode :
3282052
Title :
Optimal weighted order statistic filters under structural constraints
Author :
Nieweglowski, Jacek ; Yin, Lin ; Gabbouj, Moncef ; Neuvo, Yrjö
Author_Institution :
Signal Process. Lab., Tampere Univ. of Technol., Finland
Volume :
6
fYear :
1992
fDate :
10-13 May 1992
Firstpage :
2621
Abstract :
The authors present a procedure based on quadratic programming for finding the optimal weighted order statistic filter under the mean absolute error criterion satisfying imposed structural constraints. In this way, filters are obtained that simultaneously meet the desired detail preservation constraints and give a good noise attenuation. The algorithm is characterized by low computational complexity and simplicity in constraint formulation. The method is capable of handling large window size problems
Keywords :
computational complexity; filtering and prediction theory; quadratic programming; computational complexity; large window size problems; mean absolute error criterion; optimal weighted order statistic filter; quadratic programming; structural constraints; Adaptive filters; Adaptive signal processing; Attenuation; Cost function; Filtering; Laboratories; Nonlinear filters; Quadratic programming; Signal processing algorithms; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1992. ISCAS '92. Proceedings., 1992 IEEE International Symposium on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-0593-0
Type :
conf
DOI :
10.1109/ISCAS.1992.230683
Filename :
230683
Link To Document :
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