Autoencoder Parameter Extraction Technique for Parametric Modeling of Third-order Waveguide Filter

This paper proposes an autoencoder parameter extraction technique for parametric modeling of electromagnetic (EM) behavior of the third-order waveguide filter. In this technique, in order to extract the obtained feature parameters, the neural networks are trained to autonomously optimize the weights of the encoder and decoder. The proposed technique can extract the feature parameters more smoothly and continuously compared with the existing vector fitting technique.