Pattern recognition based on fuzzy observations for spectroscopic quality control and chromatographic fingerprinting

The quality of multicomponent samples from one or several groups of samples can be monitored by a pattern recognition method. The method is based on profiles of sample quality, which are obtained by means of a multicomponent analytical technique (e.g., ultraviolet spectroscopy or chromatography), and data reduction is done with the aid of fuzzy set theory. The advantages of the method in cases of overlapping and non-additive signals are outlined for quality control of analgesic tablets by ultraviolet spectroscopy. Its performance in the case of highly uncertain data patterns is demonstrated for classification of protein samples by chromatography.