GaN HEMT Electrothermal Modeling Using Feedback Neural Networks Technique

Thermal effect represents a main challenge for GaN high electron mobility transistor (HEMT) especially for Sisubstrate based device under high power of operation. This paper addresses this issue by developing an efficient and simple feedback neural network (FNN) based electrothermal model. The model has been applied on a packaged GaN HEMT and implemented on advanced design software (ADS). The model showed a very good agreement with large-signal measurements at different classes of operation.