A technique based on artificial neural network (ANN) is proposed to extract the electromagnetic properties of reflection-asymmetric samples from reference-plane-invariant (RPI) scattering parameter measurements. It first determines reference plane transformation… Click to show full abstract
A technique based on artificial neural network (ANN) is proposed to extract the electromagnetic properties of reflection-asymmetric samples from reference-plane-invariant (RPI) scattering parameter measurements. It first determines reference plane transformation distances and then extracts the material properties. The number of neurons in the hidden layer of the ANN model was evaluated subject to accuracy and time constraints. We examined the conformity of the dataset of the ANN model and the required time for the training process by considering different numbers of neurons in the selected hidden layer.
               
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