Graphene Field-effect Transistor Modeling Based on Artificial Neural Network
- 10.2991/meic-15.2015.339How to use a DOI?
- graphene; field-effect transistors; modeling; artificial neural network; HSPICE
Simulations and verifications on graphene electronic devices are foundations for application of graphene in integrated circuits. Modeling on graphene metal-oxide-semiconductor field-effect transistor is implemented with artificial neural network. The proposed model has high accuracy and high efficiency. The computational time for the MOSFET model is decreased significantly. More importantly, the novel model for graphene MOSFET is realized in HSPICE software as a subcircuit, which may obviously increase the efficiency of simulations on graphene large scale integrated circuits.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Guojian Cheng AU - Haiyang Wu AU - Xinjian Qiang AU - Qianyu Ji AU - Qianqian Zhao PY - 2015/04 DA - 2015/04 TI - Graphene Field-effect Transistor Modeling Based on Artificial Neural Network BT - Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering PB - Atlantis Press SP - 1479 EP - 1483 SN - 2352-5401 UR - https://doi.org/10.2991/meic-15.2015.339 DO - 10.2991/meic-15.2015.339 ID - Cheng2015/04 ER -