电子元件与材料2025，Vol.44Issue(1)：49-56,8.DOI:10.14106/j.cnki.1001-2028.2025.1472
基于改进斑马算法的GaN HEMT混合小信号建模
GaN HEMT hybrid small-signal modeling based on improved Zebra algorithm
摘要
Abstract
To enhance small-signal modeling precision of the semiconductor device and avoid the local optimum of the optimization algorithm,a hybrid small-signal modeling method for Gallium Nitride High Electron Mobility Transistor(GaN HEMT)with Improved Zebra Optimization Algorithm(IZOA)was proposed.Small-signal parameters were extracted by the mathematical correction method and the direct extraction method to establish an initial model.The improved zebra optimization algorithm was apply to further boost modeling accuracy.The Zebra Optimization Algorithm(ZOA)improvements focused on three aspects:adopt chaotic mapping for initial population diversity;apply opposition-based learning strategy to enlarge search range;employ dynamic probability values rather than fixed to balance search and convergence.The experimental results show that,the average error of direct extraction method can be decreased from 3.47%to 0.19%by IZOA.Compared with the Grey Wolf Optimizer(GWO)algorithm(average error 0.95%),it is reduced by 0.76%,and it is0.33%lower than that of the ZOA(average error 0.52%).Thus,the effectiveness and accuracy of the algorithm were verified.关键词
GaN HEMT/小信号模型/斑马优化算法/参数提取方法/改进算法Key words
GaN HEMT/small signal model/Zebra optimization algorithm/parameter extraction method/improved分类
电子信息工程引用本文复制引用
李畅,王军..基于改进斑马算法的GaN HEMT混合小信号建模[J].电子元件与材料,2025,44(1):49-56,8.基金项目
国家自然科学基金(69901003) （69901003）
四川省教育厅自然科学基金(18ZA0502) （18ZA0502）
