A neuralnetwork approach to the electromagnetic imaging of elliptic conducting cylinders
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abstract
A neural-network approach is presented for the electro-magnetic imaging of conducting cylinders of elliptical cross section. Simulation results are presented which demonstrate that a properly trained neural network is capable of accurately identifying the shape and location of unknown elliptic cylinders in inaccessible domains.