Gas mixtures IR absorption spectra decomposition using a deep neural network

Abstract

An approach to multicomponent gas mixtures IR absorption spectra decomposition using a deep neural 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.