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1 Ergebnisse
1
Machine Learning Assisted Statistical Variation Analysis of..:
, In:
2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)
,
Choe, Gihun
;
Ravindran, Prasanna Venkatesan
;
Lu, Anni
... - p. 336-337 , 2022
Link:
https://doi.org/10.1109/VLSITechnologyandCir46769.2022..
RT T1 <cTitle>2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)</cTitle>: T1 <Title>Machine Learning Assisted Statistical Variation Analysis of Ferroelectric Transistors: From Experimental Metrology to Predictive Modeling</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9830392&Exemplar=1&LAN=DE A1 Choe, Gihun A1 Ravindran, Prasanna Venkatesan A1 Lu, Anni A1 Hur, Jae A1 Lederer, Maximilian A1 Reck, Andre A1 Lombardo, Sarah A1 Afroze, Nashrah A1 Kacher, Josh A1 Khan, Asif Islam A1 Yu, Shimeng YR 2022 SN 2158-9682 K1 Training K1 Analytical models K1 Neural networks K1 Machine learning K1 Metrology K1 Very large scale integration K1 Predictive models K1 Ferroelectrics K1 Si:HfO2 K1 FeFET K1 variation K1 TKD metrology K1 TCAD K1 machine learning K1 neural network SP 336 OP 337 LK http://dx.doi.org/https://doi.org/10.1109/VLSITechnologyandCir46769.2022.9830392 DO https://doi.org/10.1109/VLSITechnologyandCir46769.2022.9830392 SF ELIB - SuUB Bremen
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