Estimation of thickness of subsurface air layer by neuron network technology application to reflected microwave signal

Neuron network technology application to subsurface air layer thickness estimation is considered. The envelope of time-domain signal was used as input data. The three-layered neuron network with backpropagation and sigmoid (S-shaped) activation function of neurons was chosen. The comparison with res...

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Bibliographic Details
Published in2008 12th International Conference on Mathematical Methods in Electromagnetic Theory pp. 150 - 152
Main Authors Drobakhin, O.O., Doronin, A.V.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2008
Subjects
Artificial neural networks
Correlation
Estimation
Neurons
Reflection
Time domain analysis
Training
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ISBN9781424422845
1424422841
ISSN2161-1734
DOI10.1109/MMET.2008.4580920

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Summary:Neuron network technology application to subsurface air layer thickness estimation is considered. The envelope of time-domain signal was used as input data. The three-layered neuron network with backpropagation and sigmoid (S-shaped) activation function of neurons was chosen. The comparison with results of correlation method is presented.
ISBN:9781424422845
1424422841
ISSN:2161-1734
DOI:10.1109/MMET.2008.4580920