Nonlinear AlGaN/GaN HEMT Model Using Multiple Artificial Neural Networks

被引：0
|
作者：
Barmuta, P. [1 ]
Plonski, P. [1 ]
Czuba, K. [1 ]
Avolio, G. [2 ]
Schreurs, D. [2 ]
机构：
[1] Warsaw Univ Technol, Warsaw, Poland
[2] Katholieke Univ Leuven, Leuven, Belgium
来源：
2012 19TH INTERNATIONAL CONFERENCE ON MICROWAVE RADAR AND WIRELESS COMMUNICATIONS (MIKON), VOLS 1 AND 2 | 2012年
关键词：
artificial neural network; temperature; GaN HEMT; nonlinear model; MESFET;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this work, a complete nonlinear-transistor-model extraction-method is described. As a case study, the AlGaN/CaN High Electron Mobility Transistor manufactured on SiC substrate is modeled. The parasitic components model is proposed, and its extraction results are presented. Low- and high-frequency large-signal measurement data are involved in order to produce multiple artificial neural networks. The network topologies of multilayer perceptron networks are established automatically. A complete learning procedure using back propagation algorithm is described. A good agreement between the measurement data and the model has been observed.
引用
收藏
页码：462 / 466
页数：5
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