Neural models of microwave transistor noise parameters based on bias conditions and S-parameters

Abstract

This paper presents the results of neural networks application in microwave transistor noise modeling. The neural networks are used to model noise parameters dependence on bias conditions and frequency. In order to improve the modeling, S-parameters are included as inputs of neural models. Once trained, the developed model can be used to predict noise parameters without additional knowledge about noise parameters or any additional computational effort.