Temperature-dependent models of low-noise microwave transistors based on neural networks

Neural networks are proposed for efficient temperature-dependent modeling of small-signal and noise performances of low-noise microwave transistors over a wide temperature range. The proposed models can be based either on neural networks only or on a combination of neural networks and empirical transistor models.