Fast and accurate modeling of embedded passives in multi-layer printed circuits using neural network approach

In this paper, we present a new approach to modeling of high-frequency effects of embedded passive components in multilayer printed circuits based on artificial neural networks. The training data are generated by electromagnetic simulators, e.g., Ansoft-HFSS and Sonnet-Lite software. The models are trained to learn the S-parameters of the embedded passives versus physical and geometrical parameters. The models are fast and represent the EM based information of the components. They can be used for efficient design of high-frequency circuits and systems.