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Pattern Recognition Based on Fuzzy Observations for Spectroscopic Quality Control and Chromatographic Fingerprinting by Matthias Otto; Hans Bandemer is a Chemistry article available to read on EtoBox.

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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 . Spectroscopic and chromatographic methods are used to characterize multicomponent samples with respect to chemical components and their concentrations . Apart from the need to report accurate component concentrations, the analyses are frequently applied to ensure the quality of a final product (e .g ., by comparing the metal pattern of a steel sample with that of a certified standard) or to classify a complex sample by means of its chromatographic profile used as a "fingerprint" . The required data-processing schemes are essentially

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Author

Matthias Otto; Hans Bandemer

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 0003-2670)

Published

1986

Language

EN

Field

Chemistry (Physical Sciences)