New pattern recognition systems designed for electronic noses

Electronic noses represent a big challenge for the pattern recognition (PAR C) systems due to several particular problems they involve. The work presen ted in this paper is targeted to develop specific methods for these kinds o f problems. One of the main issues to deal with, is the concentration varia tion, as a main cause of pattern dispersion in aroma/gas recognition. Such dispersion hinders easy cluster separation, specially for small aroma inten sities. Specific algorithms for gas identification are introduced. They cop e with the usual elongated cluster structure found in electronic noses. The PARC systems combine self-organising maps (SOM) and minimum spanning tree (MST) to build curvilinear prototypes. The method is exemplified with a min imal tin dioxide sensor array chosen for CO and CH4 detection in domestic p remises. (C) 2000 Elsevier Science S.A. All rights reserved.