限制
人工神经网络
计算机科学
功率(物理)
领域(数学)
电子工程
方案(数学)
功率半导体器件
深度学习
电压
电气工程
工程类
人工智能
机械工程
数学分析
物理
数学
量子力学
纯数学
作者
Jingyu Li,Haoyue Zhao,Hao Yuan,Fengyu Du,Zixi Wang,Xiao-Yan Tang,Qingwen Song,Yuming Zhang
标识
DOI:10.1109/led.2024.3352041
摘要
The design of device termination is crucial for power devices. In this letter, we present a novel approach for designing termination in Si-based power devices using deep neural networks (DNN), taking the narrowed field-limiting ring (NFLR) as an example. Our proposed method can not only achieve a prediction accuracy of over 97% for breakdown voltage (BV), but also provide the device optimization design scheme automatically and intelligently. We believe that the proposed machine learning technology can significantly reduce the cost and enhance the efficiency of power device design, establishing itself as a promising method for power device design.
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