Physics – Chemical Physics
Scientific paper
2010-09-02
Chemometrics and Intelligent Laboratory Systems, 2010, 103, 108-115
Physics
Chemical Physics
22 pages, 4 tables, 6 figures
Scientific paper
10.1016/j.chemolab.2010.05.023
We applied two methods of "blind" spectral decomposition (MILCA and SNICA) to quantitative and qualitative analysis of UV absorption spectra of several non-trivial mixture types. Both methods use the concept of statistical independence and aim at the reconstruction of minimally dependent components from a linear mixture. We examined mixtures of major ecotoxicants (aromatic and polyaromatic hydrocarbons), amino acids and complex mixtures of vitamins in a veterinary drug. Both MICLA and SNICA were able to recover concentrations and individual spectra with minimal errors comparable with instrumental noise. In most cases their performance was similar to or better than that of other chemometric methods such as MCR-ALS, SIMPLISMA, RADICAL, JADE and FastICA. These results suggest that the ICA methods used in this study are suitable for real life applications. Data used in this paper along with simple matlab codes to reproduce paper figures can be found at http://www.klab.caltech.edu/~kraskov/MILCA/spectra
Astakhov Sergey A.
Kraskov Alexander
Monakhova Yulia B.
Mushtakova Svetlana P.
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