Neural network data analysis for intracavity laser spectroscopy

Petr V. Nazarov; Vladimir V. Apanasovich; Katsiaryana U. Lutkovskaya; Vladimir M. Lutkovski; Pulat Y. Misakov

doi:10.1117/12.518070

3 September 2003 Neural network data analysis for intracavity laser spectroscopy

Petr V. Nazarov, Vladimir V. Apanasovich, Katsiaryana U. Lutkovskaya, Vladimir M. Lutkovski, Pulat Y. Misakov

Proceedings Volume 5135, Optical Information, Data Processing and Storage, and Laser Communication Technologies; (2003) https://doi.org/10.1117/12.518070
Event: International Conference on Lasers, Applications, and Technologies 2002, 2002, Moscow, Russian Federation

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.

Citation Download Citation

Petr V. Nazarov, Vladimir V. Apanasovich, Katsiaryana U. Lutkovskaya, Vladimir M. Lutkovski, and Pulat Y. Misakov "Neural network data analysis for intracavity laser spectroscopy", Proc. SPIE 5135, Optical Information, Data Processing and Storage, and Laser Communication Technologies, (3 September 2003); https://doi.org/10.1117/12.518070

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