Olfactory classification via interpoint distance analysis

Detection of the presence of a single prespecified chemical analyte at low concentration in complex backgrounds is a difficult application for chemica l sensors. This article considers a database of artificial nose observation s designed specifically to allow for the investigation of chemical sensor d ata analysis performance on the problem of trichloroethylene (TCE) detectio n. We consider an approach to this application which uses an ensemble of su bsample classifiers based on interpoint distances. Experimental results are presented indicating that our nonparametric methodology is a useful tool i n olfactory classification.