SPECTROSCOPIC IDENTIFICATION AND QUANTITATIVE-ANALYSIS OF BINARY-MIXTURES USING ARTIFICIAL NEURAL NETWORKS

This work deals with the application of artificial neural networks to two common problems in spectroscopy: the identification of distorted U V-visible spectra of a specific class of organic compounds, and the qu antitative determination of single components in binary mixtures of th ese compounds. The examined species were six organic indicators, whose spectra are very similar to each other; the trained networks have pro ven to be very powerful in both applications. (C) 1997 Elsevier Scienc e B.V.