Signal and noise neural models of pHEMTs

Abstract

Low-noise pHEMT transistors, that have excellent performances at microwave frequencies, can be described by their scattering and noise parameters. In this paper, a pHEMT neural model, based on multilayer perceptron neural networks is proposed. The obtained neural models can predict transistor's signal and noise performances very efficiently and accurately for a broad range of bias conditions in the operating frequency range.