Application of the neural network approach for retrieving of gas concentration from CO<sub>2</sub>-laser data

Mikhail Yu. Kataev; A. Ya. Sykhanov

doi:10.1117/12.675222

21 April 2006 Application of the neural network approach for retrieving of gas concentration from CO₂ - laser data

Mikhail Yu. Kataev, A. Ya. Sykhanov

Proceedings Volume 6160, Twelfth Joint International Symposium on Atmospheric and Ocean Optics/Atmospheric Physics; 61600E (2006) https://doi.org/10.1117/12.675222
Event: Twelfth Joint International Symposium on Atmospheric and Ocean Optics/Atmospheric Physics, 2005, Tomsk, Russian Federation

Abstract

In the report a method of atmospheric gases concentration retrieving from the C0₂-laser gas analyser data on the basis of neural networks (NN) is description. The method of neural networks is compared to the known method of the least squares most frequently meeting at processing of laser signals. One of the problems arising at processing of the lidar signals is stability of the solving (gas concentration) depending on random mistakes of measurement. A method of the neural network as have shown results of numerical modeling, it is possible to relate to a stable method of retrieving of gases concentration from C0₂-laser data.

Citation Download Citation

Mikhail Yu. Kataev and A. Ya. Sykhanov "Application of the neural network approach for retrieving of gas concentration from CO₂ - laser data", Proc. SPIE 6160, Twelfth Joint International Symposium on Atmospheric and Ocean Optics/Atmospheric Physics, 61600E (21 April 2006); https://doi.org/10.1117/12.675222

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