Neural network data analysis for intracavity laser spectroscopy

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

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)


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 solutions.


  • Atomic absorption
  • Data processing
  • Intracavity laser spectroscopy
  • Neural network


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