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Published: Journal of Chromatographic Science, Volume 36, Number 5, May 1998, pp. 237246.
A Fast Mass Spectrum Screening
Technique for Volatile Organic Compounds Based on Parallel
Artificial Neural Networks
T.G. Thomas and D.G. Smith
A technique for screening mass spectra for the presence of volatile organic compounds (VOCs) is developed using probabilistic neural networks. A parallel neural network filter is designed to recognize benzene, toluene, ethyl benzene, and o-xylene in gas chromatographymass spectrometry (GCMS) chromatograms of VOC mixtures. The filter trained rapidly and was evaluated by analyzing a variety of VOC combinations. The performance of the network offers some significant advantages over the traditional GCMS data processing techniques such as ion extraction and compound library searching. Advantages include speed, selectivity, and the ability to discriminate between overlapping compounds.
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