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Proceedings Paper

Neural network data analysis for intracavity laser spectroscopy
Author(s): Petr V. Nazarov; Vladimir V. Apanasovich; Katsiaryana U. Lutkovskaya; Vladimir M. Lutkovski; Pulat Y. Misakov
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Paper Abstract

The method of data analysis in intracavity laser spectroscopy is considered. The artificial neural network was used as an analyzing tool for the determination of elements concentration in trace amounts samples using absorption spectra. The special neural network training algorithm based on simulation of experimental spectra was developed to solve the problem of non-sufficient experimental data set. The application of this method allows achieve the better sensitivity than conventional analytical methods and proved itself more robust. The proposed method was tested on spectra of Cs water solution.

Paper Details

Date Published: 3 September 2003
PDF: 9 pages
Proc. SPIE 5135, Optical Information, Data Processing and Storage, and Laser Communication Technologies, (3 September 2003); doi: 10.1117/12.518070
Show Author Affiliations
Petr V. Nazarov, Belarusian State Univ. (Belarus)
Vladimir V. Apanasovich, Belarusian State Univ. (Belarus)
Katsiaryana U. Lutkovskaya, Belarusian State Univ. (Belarus)
Vladimir M. Lutkovski, Belarusian State Univ. (Belarus)
Pulat Y. Misakov, Institute of Molecular and Atomic Physics (Belarus)

Published in SPIE Proceedings Vol. 5135:
Optical Information, Data Processing and Storage, and Laser Communication Technologies
Jean-Pierre Goedgebuer; N. N. Rozanov; S. K. Turitsyn; Alexander S. Akhmanov; Vladislav Ya. Panchenko, Editor(s)

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