Olfactory classification via interpoint distance analysis

Author

Priebe, Carey E.

Author_Institution

Dept. of Math. Sci., Johns Hopkins Univ., Baltimore, MD, USA

Volume

23

Issue

4

fYear

2001

fDate

4/1/2001 12:00:00 AM

Firstpage

404

Lastpage

413

Abstract

Detection of the presence of a single prespecified chemical analyte at low concentration in complex backgrounds is a difficult application for chemical sensors. The article considers a database of artificial nose observations designed specifically to allow for the investigation of chemical sensor data analysis performance on the problem of trichloroethylene (TCE) detection. We consider an approach to this application which uses an ensemble of subsample classifiers based on interpoint distances. Experimental results are presented indicating that our nonparametric methodology is a useful tool in olfactory classification

Keywords

chemical sensors; fibre optic sensors; signal classification; statistical analysis; artificial nose observations; chemical analyte; interpoint distance analysis; low concentration; nonparametric methodology; olfactory classification; subsample classifiers; trichloroethylene detection; Chemical analysis; Chemical sensors; Chemical technology; Fluorescence; Nose; Olfactory; Optical arrays; Optical sensors; Optical signal processing; Sensor arrays;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.917575

Filename

917575