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
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2025
• Subjects: Engineering; Neural network; Parameter extraction
• Online Access: https://hdl.handle.net/10356/182781
• Institution: Nanyang Technological University

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...