Robustness Validation of a mm-Wave Model based on GRU Neural Networks for a GaN Power HEMT-Reference-Cited by-同舟云学术

Robustness Validation of a mm-Wave Model based on GRU Neural Networks for a GaN Power HEMT

Published:2023-10-16 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 33rd International Conference on Microelectronics (MIEL)
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Author:

Marinković Z.¹,Cai J.²,Gugliandolo G.³,Latino M.³,Fazio E.⁴,Bosi G.⁵,Raffo A.⁵,Crupi G.⁶,Donato N.³

Affiliation:

1. University of Niš,Faculty of Electronic Engineering,Department Telecommunications,Niš,Serbia,18000

2. Hangzhou Dianzi University,College of Electronics and Information,Hangzhou,China,310018

3. University of Messina,Engineering Department,Messina,Italy,98166

4. University of Messina,MIFT Department,Messina,Italy,98166

5. University of Ferrara,Engineering Department,Ferrara,Italy,44122

6. University of Messina,BIOMORF Department,Messina,Italy,98125

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10315714/10315787/10315817.pdf?arnumber=10315817

Reference11 articles.

1. GaN HEMT Modeling Using an Optimization Strategy Based on Gated Recurrent Unit Networks;cai;Proc of 2023 IEEE International Conference on Metrology for eXtended Reality Artificial Intelligence and Neural Engineering (MetroXRAINE),2023

2. A New Modeling Technique for Microwave Multicell Transistors Based on EM Simulations

3. The origin of the kink phenomenon of transistor scattering parameter S/sub 22/

4. A Comprehensive Overview of the Temperature-Dependent Modeling of the High-Power GaN HEMT Technology Using mm-Wave Scattering Parameter Measurements

5. Artificial Neural Networks for Microwave Computer-Aided Design: The State of the Art