A hybrid GaN HEMT model merging artificial neural networks and ASM-HEMT for parameter precision and scalability

• Main Authors: Lu, Zhongzhiguang, Li, Hanchao, Xie, Hanlin, Zhuang, Yihao, Wang, Wensong, Ng, Geok Ing, Zheng, Yuanjin
• 其他作者: School of Electrical and Electronic Engineering
• 格式: Article
• 語言: English
• 出版: 2025
• 主題: Engineering; Neural network; Parameter extraction
• 在線閱讀: https://hdl.handle.net/10356/182781

An innovative hybrid physical model for gallium nitride high-electron-mobility transistors (GaN HEMTs) that leverages an artificial neural network (ANN) approach is proposed. This model utilizes ANN to formulate surface potentials, correlating them with the device’s RF and dc behaviors in accordance...