Inversion of absorption spectral data for relaxation matrix determination. I. Application to line mixing in the 106←000 overtone transition of HCN

1998 ◽  
Vol 108 (2) ◽  
pp. 392-401 ◽  
Author(s):  
Robert Boyd ◽  
Tak-San Ho ◽  
Herschel Rabitz ◽  
Daniele Romanini ◽  
Kevin Lehmann
Keyword(s):  
Spectral Data ◽  
Relaxation Matrix ◽  
Line Mixing

Modelling of the rotational relaxation matrix in line-mixing effect calculations

2004 ◽  
Vol 102 (16-17) ◽  
pp. 1843-1850 ◽  
Author(s):  
A. V. Domanskaya ◽  
N. N. Filippov ◽  
N. M. Grigorovich ◽  
M. V. Tonkov *
Keyword(s):  
Rotational Relaxation ◽  
Mixing Effect ◽  
Relaxation Matrix ◽  
Line Mixing

Estimating Pigment Concentrations from Spectral Images Using an Encoder‐Decoder Neural Network

2020 ◽  
Vol 64 (3) ◽  
pp. 30502-1-30502-15
Author(s):  
Kensuke Fukumoto ◽  
Norimichi Tsumura ◽  
Roy Berns
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Absorption Coefficient ◽  
Spectral Data ◽  
High Accuracy ◽  
Pigment Concentration ◽  
Scattering Coefficient ◽  
A Value ◽  
Input And Output ◽  
Pigment Concentrations

Abstract A method is proposed to estimate the concentration of pigments mixed in a painting, using the encoder‐decoder model of neural networks. The model is trained to output a value that is the same as its input, and its middle output extracts a certain feature as compressed information about the input. In this instance, the input and output are spectral data of a painting. The model is trained with pigment concentration as the middle output. A dataset containing the scattering coefficient and absorption coefficient of each of 19 pigments was used. The Kubelka‐Munk theory was applied to the coefficients to obtain many patterns of synthetic spectral data, which were used for training. The proposed method was tested using spectral images of 33 paintings, which showed that the method estimates, with high accuracy, the concentrations that have a similar spectrum of the target pigments.

Detection of potential aircraft icing regions with GOES multi-spectral data

1997 ◽  
Author(s):  
Gary Ellrod ◽  
James Nelson, III ◽  
Gary Ellrod ◽  
James Nelson, III
Keyword(s):  
Spectral Data ◽  
Aircraft Icing
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