Application of theKarhunen-LoeveExpansion toFeatureSelection and Ordering

The Karhunen-Lo6ve expansion hasbeenusedpre- viously toextract important features forrepresenting samples taken fromagiven distribution. A methodisdeveloped herein tousethe Karhunen-Loeve expansion toextract features relevant toclassifica- tion ofasample takenfromoneoftwopattern classes. Numerical examples arepresented toillustrate thetechnique. Also, itisshownthat theproperties oftheproposed technique can beapplied tounsupervised clustering, wheregivensamples are classified into twoclasses without apriori knowledge oftheclass. IndexTerms-Clustering, feature extraction, feature selection, Karhunen-Loeve expansion, pattern recognition, unsupervised learn- ing.