Development of a Neural Approach for Bias-Dependent Scalable Small-Signal Equivalent Circuit Modeling of GaAs HEMTs

被引：0

作者：

Marinkovic, Zlatica ^{[1
]}

Crupi, Giovanni ^{[2
]}

Caddemi, Alina ^{[2
]}

Markovic, Vera ^{[1
]}

机构：

[1] Univ Nis, Fac Elect Engn, Aleksandra Medevedeva 14, Nish 18000, Serbia

[2] Univ Messina, Dipartimento Fis Mat & Ingn Elettorn, I-98166 Messina, Italy

来源：

2010 EUROPEAN MICROWAVE INTEGRATED CIRCUITS CONFERENCE (EUMIC) | 2010年

关键词：

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：

This paper presents an approach for small-signal modeling of microwave FETs. The model is based on an equivalent circuit whose elements are extracted by an analytical approach. In order to make model bias-dependent and scalable, artificial neural networks are exploited for modeling of the dependence of the equivalent circuit elements on the bias voltages and the transistor gate width. The proposed approach is exemplified on modeling of three scaled on-wafer GaAs HEMT devices.

引用

页码：182 / 185

页数：4

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