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Discrimination of trace plastic explosives using neural networks

This paper is intended to describe the approach to data processing used on a prototype portable explosive detector/analyzer based on gas chromatography. The emphasis is on achieving more reliable analysis without intervention from an expert user. Neural networks have been used to overcome some of the problems encountered using conventional data processing algorithms. The aim has been to produce a system which embodies expert-like knowledge so that sophisticated judgments may be made when the system is operated by staff with minimal training.