Title :
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
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;
Conference_Titel :
Telecommunications in Modern Satellite, Cable and Broadcasting Service, 2003. TELSIKS 2003. 6th International Conference on
Print_ISBN :
0-7803-7963-2
DOI :
10.1109/TELSKS.2003.1246289
