Recent Advances in EM Parametric Modeling Using Combined Neural Network and Transfer Function

This paper provides an overview of the recent advances in electromagnetic (EM) modeling approaches using combined neural network and transfer function (neuro-transfer function or neuro-TF) and its application to antenna design. In this technique, neural networks are trained to learn the relationship between pole/residues of the transfer functions and geometrical parameters. After the modeling process, the trained model can be used to provide accurate and fast prediction of the EM behavior with geometrical parameters as variables. This technique is illustrated by a example of EM parametric modeling of an ultra-wideband antenna.

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