Comparative Analysis of Different ANN Methods for the Noise Wave Temperature Extraction

Abstract

The noise wave temperatures are extracted from the measured transistor noise parameters usually using time-demanding optimization procedures in microwave circuit simulators. For more efficient extraction of these temperatures, we developed four different extraction methods based on artificial neural networks. The developed extraction methods are compared in terms of accuracy, complexity and effectiveness in the case of GaAs HEMT device.