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Gas mixtures IR absorption spectra decomposition using a deep neural network V. V. Prischepa, V. E. Skiba, D. A. Vrazhnov, Yu. V. Kistenev

Contributor(s): Prischepa, Vladimir V | Skiba, V. E | Vrazhnov, Denis A | Kistenev, Yury VMaterial type: ArticleArticleContent type: Текст Media type: электронный Subject(s): многокомпонентные газовые смеси | обратная задача спектроскопии | разложение спектров поглощения смесиGenre/Form: статьи в журналах Online resources: Click here to access online In: Journal of Quantitative Spectroscopy and Radiative Transfer Vol. 301. P. 108521 (1-10)Abstract: An approach to multicomponent gas mixtures IR absorption spectra decomposition using a deep neu- ral network was developed. The process of refinement and optimization of the absorption spectra data model to improve the accuracy of the inverse spectroscopic task solution is described. A criterion for the reliability of restoring the concentration of an individual component in a gas mixture based on its share of the area under the absorption spectrum curve was suggested and tested.
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An approach to multicomponent gas mixtures IR absorption spectra decomposition using a deep neu- ral network was developed. The process of refinement and optimization of the absorption spectra data model to improve the accuracy of the inverse spectroscopic task solution is described. A criterion for the reliability of restoring the concentration of an individual component in a gas mixture based on its share of the area under the absorption spectrum curve was suggested and tested.

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