New neural method for bias dependent noise modelling of microwave transistors

Abstract

A new method for accurate determination of noise parameters of microwave transistors for various bias conditions is proposed in this paper. The proposed model consists of a transistor empirical noise model (modification of Pospieszalski’s noise model) and two artificial neural networks. With the aim to avoid extraction of the empirical model parameters for each bias point, an artificial neural network is used to introduce bias-dependence of the equivalent circuit parameters. Accuracy of such bias-dependent model is further improved by using an additional neural network aimed to correct the noise parameters’ values. The proposed modeling approach is exemplified by modelling of a MESFET device in packaged form. The noise parameters obtained by the simulation agree well with the measured data.