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Detection and classification of buried dielectric anomalies using neural networks-further results

โœ Scribed by Azimi-Sadjadi, M.R.; Stricker, S.A.


Book ID
114542826
Publisher
IEEE
Year
1994
Tongue
English
Weight
696 KB
Volume
43
Category
Article
ISSN
0018-9456

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An analysis of the performances of the neural-network approach for the geometric and dielectric characterization of buried cylinders is carried out. The neural-network process data are obtained from the time-domain formulation of the electromagnetic scattering problem. This analysis is based on the