Multi-parameter Modeling Technique Based on TF-ANN for FSS Design

In this communication, a novel TF-ANN model is proposed for parametric modeling of the frequency selective structure (FSS). In the proposed model, the pole-residue-based transfer function(TF) is used to fit the frequency responses of the training samples. The introduction of the modified response improves the robustness of the TF-ANN model for FSS and solves the order-changing of the transfer function between different samples. Then, the ANN is used to learn the nonlinear relationship between the physical parameters and the coefficients of the transfer function. Finally, two wideband FSSs are used as the examples to validate the effectiveness of the proposed model. The modeling results show that the proposed model is a good candidate to accelerate the design and optimization processes of the FSS without using any exact empirical model.