On the large-signal modeling of AlGaN/GaN devices using genetic neural networks

Author

Jarndal, Anwar ; Pillai, S. ; Abdulqader, H. ; Kompa, G.

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Nizwa, Nizwa, Oman

fYear

2012

Firstpage

60

Lastpage

63

Abstract

An accurate large-signal model for AlGaN-GaN HEMT is presented. This model is derived from a distributed small-signal model that efficiently describes the physics of the device. A genetic neural network based model for the gate and drain currents and charges is presented along with its parameters extraction procedure. The model shows very good results for simulating the high-power operation of a 8×125-μm gate width AlGaN/GaN HEMT and the associated nonlinearities even beyond the 1-dB gain compression point.

Keywords

III-V semiconductors; aluminium compounds; electronic engineering computing; gallium compounds; high electron mobility transistors; neural nets; semiconductor device models; wide band gap semiconductors; AlGaN-GaN; HEMT; distributed small-signal model; drain current; gain compression point; gate current; genetic neural network-based model; large-signal modeling; parameter extraction procedure; Charge carrier processes; Dispersion; Gallium nitride; HEMTs; Logic gates; Neural networks; Optimization; GaN HEMT; genetic optimization; high power device; large-signal modeling; neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Microwave Integrated Circuits Conference (EuMIC), 2012 7th European

Conference_Location

Amsterdam

Print_ISBN

978-1-4673-2302-4

Electronic_ISBN

978-2-87487-026-2

Type

conf

Filename

6483735