An Accurate Neural Network-Based Consistent Gate Charge Model for GaN HEMTs by Refining Intrinsic Capacitances-Reference-Cited by-同舟云学术

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An Accurate Neural Network-Based Consistent Gate Charge Model for GaN HEMTs by Refining Intrinsic Capacitances

Published:2021-07 Issue:7 Volume:69 Page:3208-3218
ISSN:0018-9480
Container-title:IEEE Transactions on Microwave Theory and Techniques
language:
Short-container-title:IEEE Trans. Microwave Theory Techn.

Author:

Hu Wenrui^ORCID,Luo Haorui^ORCID,Yan Xu^ORCID,Guo Yong-Xin^ORCID

Funder

National Research Foundation (NRF) of Singapore

Jiangsu Province Science and Technology Department

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Radiation

Link

http://xplorestaging.ieee.org/ielx7/22/9471031/09428010.pdf?arnumber=9428010

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3. Artificial neural network models for metal-ferroelectric-insulator-semiconductor ferroelectric tunnel junction memristor;Microelectronics Journal;2024-02

4. Passive clamping driver circuit for suppressing positive and negative gate crosstalk in GaN HEMTs;Journal of Power Electronics;2024-01-29

5. A Knowledge-Guided Neural Network-Based Large-Signal Model for InP HBTs With Self-Heating Effect Consideration;IEEE Transactions on Microwave Theory and Techniques;2024

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