DocumentCode :
1116739
Title :
Robust Multidimensional Matched Subspace Classifiers Based on Weighted Least-Squares
Author :
Salberg, Arnt-Børre ; Hanssen, Alfred ; Scharf, Louis L.
Author_Institution :
DolphiScan AS, Moelv
Volume :
55
Issue :
3
fYear :
2007
fDate :
3/1/2007 12:00:00 AM
Firstpage :
873
Lastpage :
880
Abstract :
We propose and design two classes of robust subspace classifiers for classification of multidimensional signals. Our classifiers are based on robust M-estimators and the least-median-of-squares principle, and we show that they may be unified as iterated reweighted oblique subspace classifiers. The performance of the proposed classifiers are demonstrated by two examples: noncoherent detection of space-time frequency-shift keying signals, and shape classification of partially occluded two-dimensional (2-D)_ objects. In both cases, the proposed robust subspace classifiers outperform the conventional subspace classifiers
Keywords :
least squares approximations; multidimensional signal processing; signal classification; signal detection; least-median-of-squares principle; multidimensional signals classification; robust multidimensional matched subspace classifiers; signals noncoherent detection; space-time frequency-shift keying signals; weighted least-squares; Detectors; Frequency shift keying; Gaussian noise; Interference; Multidimensional systems; Noise robustness; Object detection; Pattern recognition; Shape; Signal design; Noncoherent receivers; robust estimation; shape recognition; subspace classification;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2006.887560
Filename :
4099572
Link To Document :
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