Small‐signal modeling of microwave transistors using radial basis function artificial neural network‐comparison of different methods for spread constant determined-Reference-Cited by-同舟云学术

Small‐signal modeling of microwave transistors using radial basis function artificial neural network‐comparison of different methods for spread constant determined

Published:2022-03-15 Issue:6 Volume:32 Page:
ISSN:1096-4290
Container-title:International Journal of RF and Microwave Computer-Aided Engineering
language:en
Short-container-title:Int J RF Mic Comp-Aid Eng

Author:

Qi Junjun¹^ORCID,Lu Hongliang¹^ORCID,Yan Silu¹,Zhao Ranran¹,Tan Daidao¹,Zhang Yuming¹,Zhang Yimen¹

Affiliation:

1. Key Laboratory of Wide Band‐Gap Semiconductor Materials and Devices School of Microelectronics, Xidian University Xi'an China

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Computer Science Applications

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mmce.23145

Reference35 articles.

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3. An Accurate Neural Network-Based Consistent Gate Charge Model for GaN HEMTs by Refining Intrinsic Capacitances

4. Z.Marinković GiovanniCrupi AntonioRaffo et al.A neural network approach for nonlinear modelling of LDMOSFETs. 2014 International Workshop on Integrated Nonlinear Microwave and Millimetre‐wave Circuits (INMMiC); 2014:1‐3

5. Optimization of Small-Signal Model of GaN HEMT by Using Evolutionary Algorithms

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