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

页码：462 / 466

页数：5

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