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

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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Bibliographic Details
Main Authors: Zegen Zhu, Gianni Bosi, Antonio Raffo, Giovanni Crupi, Jialin Cai
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of the Electron Devices Society
Subjects:
GaN HEMT
GRU
kink effect
machine learning methods
semiconductor device modeling
scattering parameter measurements
Online Access:https://ieeexplore.ieee.org/document/10433010/

Internet

https://ieeexplore.ieee.org/document/10433010/

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