Title :
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
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;
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
