Accurate Modeling of the Special Microwave Structures Using Artificial Neural Networks

Nowadays, there are many various microwave structures for which their nonlinear models for CAD are necessary. However, in the recent PSpice family programs, only a class of five types of MESFET model is available. In the paper, a way is suggested for modeling miscellaneous microwave structures by exclusive neural networks, or corrective neural networks working attached to an updated analytic model. The accuracy of both procedures is assessed by extracting model parameters in static and dynamic domains: first, an approximation of the AlGaAs/InGaAs/GaAs pHEMT output characteristics is carried out by the corrective neural network; and second, an approximation of the capacitance function of the InGaAs/InP avalanche photodiode is performed by the exclusive neural network. A sequence of analyses is also performed for determining optimal structure of the artificial neural network