2D Spectral Transposed Convolutional Neural Network for S-Parameter Predictions

In packaging problems, S-parameter predictions are necessary. Machine learning methods lead to dimensionality related challenges which we address here through spectral trans-posed convolutional neural network using 2D kernels. Results show that Normalized Mean-squared Error (NMSE) dropped 0.002 by using 53.7% of the parameters.