Spectroscopic identification and quantitative analysis of binary mixtures using artificial neural networks

被引：7

作者：

Ganadu, ML ^{[1
]}

Lubinu, G ^{[1
]}

Tilocca, A ^{[1
]}

Amendolia, SR ^{[1
]}

机构：

[1] UNIV SASSARI,IST MATEMAT & FIS,I-07100 SASSARI,ITALY

来源：

TALANTA | 1997年 / 44卷 / 10期

关键词：

mixtures; networks; neural; spectra;

D O I：

10.1016/S0039-9140(97)00088-X

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

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

引用

页码：1901 / 1909

页数：9

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[3]

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[4]

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