Advanced Neural Network Techniques for GaN-HEMT Dynamic Behavior Characterization

Author

Orengo, G. ; Colantonio, P. ; Giannini, F. ; Pirola, M. ; Camarchia, V. ; Guerrieri, S. Donati

Author_Institution

Dept. of Electron. Eng., Tor Vergata Univ., Roma

fYear

2006

fDate

10-13 Sept. 2006

Firstpage

249

Lastpage

252

Abstract

This paper presents a new approach to build RF dynamic behavioral models, based on time-delay neural networks (TDNNs), suitable for FET devices, and capable to identify the working class and to characterize both short- and long-term device memory, through a time-domain training procedure, for a wide range of input power levels. The presented model has been effectively applied to GaN-based devices, working in class A, AB and B

Keywords

III-V semiconductors; gallium compounds; high electron mobility transistors; neural nets; semiconductor device models; wide band gap semiconductors; FET devices; GaN; GaN-HEMT dynamic behavior characterization; RF dynamic behavioral models; device memory; high electron mobility transistor; thermal model; time-delay neural networks; time-domain training procedure; Delay effects; Finite impulse response filter; Intrusion detection; Network synthesis; Neural networks; Neurons; Nonlinear filters; Radio frequency; Sampling methods; Time domain analysis; Dynamic behavioral model; GaN; Neural Network; Thermal model;

fLanguage

English

Publisher

ieee

Conference_Titel

European Microwave Integrated Circuits Conference, 2006. The 1st

Conference_Location

Manchester

Print_ISBN

2-9600551-8-7

Type

conf

DOI

10.1109/EMICC.2006.282799

Filename

4057622