Empirical model generation techniques for planar microwave components using electromagnetic linear regression models

Two empirical model generation techniques of microwave devices, for a large range of geometric and material parameters opportunely chosen, are presented. The empirical models are based on multiple linear regression approach, which compensates the error between an initial inaccurate empirical model and an electromagnetic full-wave solver by means of neuromodeling-based methods. The aim of these techniques is to generate accurate empirical models, which are computationally very efficient with respect to any electromagnetic technique. These simple models could be integrated in a toolbox of any commercially available computed-aided design (CAD) tools for RF/microwave circuits. The two techniques are here tested for a tunable microwave phase shifter.