Neural approach for temperature‐dependent modeling of GaN HEMTs. (25th June 2014)

• Record Type: Journal Article
• Authors: Marinković, Zlatica; Crupi, Giovanni; Caddemi, Alina; Avolio, Gustavo; Raffo, Antonio; Marković, Vera; Vannini, Giorgio; Schreurs, Dominique M. M.‐P.
• Is Part Of: International journal of numerical modelling. Volume 28:Number 4(2015:Jul./Aug.)
• Page Start: 359
• Page End: 370
• Publication Date: 2014-06-25
• Subjects: Electric networks -- Mathematical models -- Periodicals; Electronics -- Mathematical models -- Periodicals; 621.3011
• DOI: 10.1002/jnm.2011
• Languages: English
• ISSNs: 0894-3370

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Gallium nitride high electron‐mobility transistors have gained much interest for high‐power and high‐temperature applications at high frequencies. Therefore, there is a need to have the dependence on the temperature included in their models. To meet this challenge, the present study presents a neural approach for extracting a multi‐bias model of a gallium nitride high electron‐mobility transistors including the dependence on the ambient temperature. Accuracy of the developed model is verified by comparing modeling results with measurements. Copyright © 2014 John Wiley &amp; Sons, Ltd.</p> </abstract>