アプリケーションギャラリ

This example builds surrogate models with deep neural network (DNN) training to quickly estimate the performance of a microstrip patch antenna based on four design parameters: patch length, tuning stub length, dielectric constant of a substrate, and frequency. The model also simulates a full finite element (FEM) model using asymptotic waveform evaluation of the computed S-parameters to efficiently evaluate the frequency response with fine frequency resolution. This approach can be much faster than a conventional discrete frequency sweep, which may take a long time due to the large number of samples. The full model is used to verify the accuracy of the surrogate models.