doi: 10.7763/IJMO.2012.V2.200
Application of Adaptive Neuro-Fuzzy Inference System for Predictaion of HEMT Transistor Noise Parameters
M. Hayati
1
,
A. Rezaei
2
- 1 Electrical Engineering Department, Faculty of Engineering, Razi University, Kermanshah-67149, Iran.
- 2 Electrical Engineering Department, Kermanshah University of technology, Kermanshah, Iran.
Abstract
In this paper, simulation of HEMT Transistor Noise Parameters such as minimum noise figure, normalized equivalent resistance, magnitude of optimum reflection coefficient and angle of optimum reflection coefficient dependence on bias conditions such as dc drain-to-source voltage, dc drain-to-source current, frequency and Sparameters using ANFIS model is carried out. This model can accurately predict transistor noise parameters in a wide frequency ranges for all bias points from the operating range including transistor S-parameters. The proposed models can be used as efficient tools for noise modeling of HEMT transistor.
Keywords
- HEMT transistor
- adaptive neuro-fuzzy inference system
- high electron mobility transistor
- sparameter
- noise modeling
How to Cite
M. Hayati and A. Rezaei, "Application of Adaptive Neuro-Fuzzy Inference System for Predictaion of HEMT Transistor Noise Parameters," International Journal of Modeling and Optimization, vol. 2, no. 5, pp. 641-643, 2012. https://doi.org/ 10.7763/IJMO.2012.V2.200
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).