Small signal and large signal modeling of HBT´s using neural networks

Author

Munshi, Kambiz ; Vempada, Pradeep ; Prasad, Sheila ; Sönmez, Ertugrul ; Schumacher, Hermann

Author_Institution

Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA

Volume

2

fYear

2003

fDate

1-3 Oct. 2003

Firstpage

565

Abstract

This paper presents the small signal and large signal models for an AlGaAs and a SiGe heterojunction bipolar transistor, using neural network techniques. The main advantage of this technique is the wide range of frequencies over which the small signal model is valid and the great accuracy of the large signal characteristics. Both the models have been verified by comparing the simulated values with the measured ones of the HBTs for both the material systems.

Keywords

III-V semiconductors; aluminium compounds; gallium arsenide; germanium compounds; heterojunction bipolar transistors; neural nets; silicon compounds; AlGaAs; HBT; SiGe; heterojunction bipolar transistor; large signal modeling; neural networks; small signal modeling; Computational modeling; Computer networks; Feedforward neural networks; Frequency; Germanium silicon alloys; Heterojunction bipolar transistors; Multi-layer neural network; Neural networks; Scattering parameters; Silicon germanium;

fLanguage

English

Publisher

ieee

Conference_Titel

Telecommunications in Modern Satellite, Cable and Broadcasting Service, 2003. TELSIKS 2003. 6th International Conference on

Print_ISBN

0-7803-7963-2

Type

conf

DOI

10.1109/TELSKS.2003.1246289

Filename

1246289