A Scalable Knowledge-Based Neural Network Model for GaN HEMTs With Accurate Trapping and Self-Heating Effects Characterization-Reference-Cited by-同舟云学术

A Scalable Knowledge-Based Neural Network Model for GaN HEMTs With Accurate Trapping and Self-Heating Effects Characterization

Published:2023-09 Issue:9 Volume:71 Page:3747-3760
ISSN:0018-9480
Container-title:IEEE Transactions on Microwave Theory and Techniques
language:
Short-container-title:IEEE Trans. Microwave Theory Techn.

Author:

Li Mengjie¹,Zhang Qi-Jun²^ORCID,Feng Feng¹^ORCID,Li Zhao¹,He Tianwei³,Zhong Sheng³,Ma Kaixue¹^ORCID

Affiliation:

1. Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, School of Microelectronics, Tianjin University, Tianjin, China

2. Department of Electronics, Carleton University, Ottawa, ON, Canada

3. Department of Engineering Physics, Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

Key Research and Development and Transformation Project of Qinghai Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Radiation

Link

http://xplorestaging.ieee.org/ielx7/22/10241248/10058706.pdf?arnumber=10058706

Reference69 articles.

1. An Evolutionary Multilayer Perceptron-Based Large-Signal Model of GaN HEMTs Including Self-Heating and Trapping Effects

2. An accurate small-signal model for AlGaN-GaNHEMT suitable for scalable large-signal model construction

3. Large-Signal Model for AlGaN/GaN HEMTs Accurately Predicts Trapping- and Self-Heating-Induced Dispersion and Intermodulation Distortion

4. A reliable optimization-based model parameter extraction approach for GaAs-based FET’s using measurement-correlated parameter starting values;mwema,2002

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