DocumentCode
2466045
Title
Modeling nanoscale MOSFETs by a neural network approach
Author
Fang, Min ; He, Jin ; Zhang, Jian ; Zhang, Lining ; Chan, Mansun ; Ma, Chenyue
Author_Institution
Shenzhen Grad. Sch., Peking Univ., Shenzhen
fYear
2008
fDate
8-10 Dec. 2008
Firstpage
1
Lastpage
4
Abstract
This paper presents modeling nanometer MOSFETs by a neural network approach. The principle of this approach is firstly introduced and its application in modeling DC and conductance characteristics of nano-MOSFET is demonstrated in details. It is shown that this approach does not need parameter extraction routine while its prediction of the transistor performance has a small relative error within 1% compared with measure data, thus its result is as accurate as that BSIM model.
Keywords
MOSFET; backpropagation; neural nets; semiconductor device models; nanoscale MOSFET; neural network approach; Circuit analysis; Helium; MOSFETs; Nanoscale devices; Neural networks; Neurons; Parameter extraction; Predictive models; Semiconductor device modeling; Threshold voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Electron Devices and Solid-State Circuits, 2008. EDSSC 2008. IEEE International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-2539-6
Electronic_ISBN
978-1-4244-2540-2
Type
conf
DOI
10.1109/EDSSC.2008.4760660
Filename
4760660
Link To Document