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The process of identifying unknown hidden objects by taking advantage of electromagnetic effects becomes more and more important. Clearing of mines or finding electrical conductors in concrete should be mentioned here. Magnetisation and eddy currents are the phenomena which are used in general. In this case, the layout and arrangement of the excitation coils and receiving coils influences the effectiveness and accuracy crucially. This design optimization process can be done by simulating the electromagnetic field with a 3D finite element method. Once a satisfying configuration has been found, the question arises, which quantities of the measured (and hence simulated) signals contain the most reliable information? Since the 3D finite element calculations are very time consuming, the inverse problem (detecting the ferrous object from some measured signals) is performed by approximating the corresponding electromagnetic signal by a neural network. Investigations on a ferrous conductive rod will be described in the paper.

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