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General Information
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2012 Vol.2(5): 641-643 ISSN: 2010-3697
DOI: 10.7763/IJMO.2012.V2.200

Application of Adaptive Neuro-Fuzzy Inference System for Predictaion of HEMT Transistor Noise Parameters

M. Hayati and A. Rezaei

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.

Index Terms—HEMT transistor, adaptive neuro-fuzzy inference system, high electron mobility transistor, sparameter, noise modeling.

M. Hayati is with the Electrical Engineering Department, Faculty of Engineering, Razi University, Kermanshah-67149, Iran (email: mohsen_hayati@yahoo.com).
A. Rezaei is with the Electrical Engineering Department, Kermanshah University of technology, Kermanshah, Iran (email: arezaei818@yahoo.com).


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.

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