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Neural network electrothermal modeling approach for microwave active devices
Author(s) -
Jarndal Anwar
Publication year - 2019
Publication title -
international journal of rf and microwave computer‐aided engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.335
H-Index - 39
eISSN - 1099-047X
pISSN - 1096-4290
DOI - 10.1002/mmce.21764
Subject(s) - signal (programming language) , artificial neural network , feed forward , microwave , computer science , small signal model , transistor , thermal , feedforward neural network , electronic engineering , materials science , electrical engineering , engineering , physics , artificial intelligence , control engineering , telecommunications , voltage , meteorology , programming language
This article presents an artificial neural network (ANN) approaches for small‐ and large‐signal modeling of active devices. The small‐signal characteristics were modeled by S‐parameters based feedforward NN models. The models have been implemented to simulate the bias, frequency and temperature dependence of measured S‐parameters. Feedback NN based large‐signal model was developed and implemented to simulate the drain current and its inherent thermal effect due to self‐heating and ambient temperature. Both small‐ and large‐signal models have been validated by measurements for 100‐μm and 1‐mm GaN high electron mobility transistors and very good agreement was obtained.