@inproceedings{8b70a4cb2c0d4bab9721d6134f19f026,
title = "High frequency HEMT modeling using artificial neural network technique",
abstract = "Accurate high frequency modeling for active devices which includes microwave diodes and transistors are absolutely necessary for computer-aided radio frequency integrated circuit (RFIC) design. This paper aims to provide an overview on small signal and large signal for field effect transistor (FETs) based on the combination of the conventional equivalent circuit modeling and artificial neural network (ANN) modeling techniques. MLPs and Space-mapped neuromodeling techniques have been used for building a small signal model, and the adjoint technique as well as integration and differential techniques are used for building a large signal model. Experimental results, which confirm the validity of the approaches, are also presented.",
keywords = "ANN, device, modeling",
author = "Jianjun Gao and Li Shen and Danting Luo",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2015 ; Conference date: 11-08-2015 Through 14-08-2015",
year = "2015",
doi = "10.1109/NEMO.2015.7415085",
language = "英语",
series = "Proceedings of 2015 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of 2015 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2015",
address = "美国",
}