DocumentCode :
3730402
Title :
By using grey system and Neural-Fuzzy Network methods to obtain the threshold voltage of submicron n-MOSFET DUTs
Author :
Shen-Li Chen; Dun-Ying Shu
Author_Institution :
Department of Electronic Engineering, National United University, Miaoli City 36063, Taiwan
fYear :
2015
Firstpage :
501
Lastpage :
505
Abstract :
In this paper, two techniques are used to obtain the complex non-linear threshold voltage (Vth) data in sub-micrometer MOSFET DUTs via the grey system (GS) method and Neural-Fuzzy Network (NFN). This paper presents the implement procedure of these two models in Vth predictions. Moreover, comparisons among the GS and NFN output results are carried out. Here, it will be used to analyze the Vth inclination of submicron MOSFET DUTs due to the device geometric effect. Introducing comparison between the measured and prediction characteristics of Vth show good matching for a wide domain of channel width (W), length (L), and bias conditions. Then, the implemented procedure may be proper for BSIM model parameters extraction.
Keywords :
"MOSFET","Predictive models","Threshold voltage","Logic gates","Computational modeling","Conferences","Adaptation models"
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on
Type :
conf
DOI :
10.1109/FSKD.2015.7381993
Filename :
7381993
Link To Document :
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