CLASSIFICATION OF PYROLYSIS MASS-SPECTRA OF BIOLOGICAL-MATERIALS USING CONVEX CONES

This work addresses the classification of high-dimensional time-depend ent pyrolysis mass spectra of biological samples. The aim was the dete ction and classification of biological agents, and the developed appro ach resembles mixture analysis. The data were projected on to a low-di mensional subspace using singular value decomposition. Then a convex c one was formed on this subspace, showing as its corners physically mea ningful components of the sample. This technique enabled separation of a biological material signal largely independent of the absolute amou nt of sample. The detection of the presence of any biological material could be accomplished based on the convex cone alone, without other r eference to the mass spectra. Automated clustering of samples was succ essfully carried out using a minimal spanning tree.