Implementation of temperature dependence in small-signal models of microwave transistors including noise

In this paper, the artificial neural network approach is proposed for prediction purposes of temperature behavior of microwave transistors. Neural networks are used for modeling of temperature dependencies of elements of transistor small-signal models including noise. These dependencies are extracted from transistor signal and noise data referred to a set of temperatures. The developed models are valid in the whole operational range of temperatures.