Neural network modeling of active devices for use in MMIC design

Abstract

This work can be classified into three parts: The first part is a multidimensional signal–noise neural network model for a microwave small-signal transistor. Here the device is modeled by a black box, whose small signal and noise parameters are evaluated through a neural network, based upon the fitting of both these parameters for multiple bias and configuration with their target values. The second part is the computer simulation of the possible performance (F,Vi,Gtmax) triplets. In the final part, which is the combination of the first two parts, the performance curves are obtained using the relationships among operation conditions f, VCE, and ICE; the noise figure, input VSWR and maximum stable transducer gain.