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1
Degradation Trajectory Tracking of MOSFETs Based on Machine..:
, In:
2023 5th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)
,
Li, Zhaorui
;
Shi, Dongqiang
;
Zhang, Ying
... - p. 1148-1152 , 2023
Link:
https://doi.org/10.1109/ICMSP58539.2023.10170830
RT T1 <cTitle>2023 5th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)</cTitle>: T1 <Title>Degradation Trajectory Tracking of MOSFETs Based on Machine Learning and CEEMDAN</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10170830&Exemplar=1&LAN=DE A1 Li, Zhaorui A1 Shi, Dongqiang A1 Zhang, Ying A1 Li, Kai A1 Gui, Huazhan A1 Yuan, Feng YR 2023 K1 Degradation K1 MOSFET K1 Trajectory tracking K1 Thermal decomposition K1 Market research K1 Power electronics K1 Thermal noise K1 power MOSFETs K1 Deep extreme learning machine K1 CEEMDAN K1 degradation trend prediction SP 1148 OP 1152 LK http://dx.doi.org/https://doi.org/10.1109/ICMSP58539.2023.10170830 DO https://doi.org/10.1109/ICMSP58539.2023.10170830 SF ELIB - SuUB Bremen
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