Accurate Modeling of GaN HEMTs Oriented to Analysis of Kink Effects in S<sub>22</sub> and h<sub>21</sub>: An Effective Machine Learning Approach
In this work, for the first time, a machine learning behavioral modeling methodology based on gate recurrent unit (GRU) is developed and used to model and then analyze the kink effects (KEs) in the output reflection coefficient <inline-formula> <tex-math notation="LaTeX">$(S_{2...
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Main Authors: | Zegen Zhu, Gianni Bosi, Antonio Raffo, Giovanni Crupi, Jialin Cai |
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Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
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Series: | IEEE Journal of the Electron Devices Society |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10433010/ |
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