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Peer-reviewedCC BYMicromachines

Deep Neural Network-Driven Reliability Assessment Methodology for Total Ionizing Dose Effects in FDSOI MOSFETs

  • Hanying Deng1
  • Yu Wang2
  • Jinshun Bi2
  • Jianbin Jiao1
  • Yue Ma3
  • Baihong Chen3
  • Yundong Xuan1
  1. 1Department of Circuits, School of Emergency Management Science and Engineering, , Beijing 100049, China; (H.D.); (J.J.)
  2. 2School of Integrated Circuits, , Guiyang 550025, China;
  3. 3Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China; (Y.M.); (B.C.)
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Cite

BibTeXRIS
BibTeX
@article{deng2026deep,
  title = {{Deep Neural Network-Driven Reliability Assessment Methodology for Total Ionizing Dose Effects in FDSOI MOSFETs}},
  author = {Hanying Deng and Yu Wang and Jinshun Bi and Jianbin Jiao and Yue Ma and Baihong Chen and Yundong Xuan},
  journal = {Micromachines},
  year = {2026},
  month = sep,
  url = {https://europepmc.org/article/PMC/PMC13707749},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Deep Neural Network-Driven Reliability Assessment Methodology for Total Ionizing Dose Effects in FDSOI MOSFETs
AU  - Hanying Deng
AU  - Yu Wang
AU  - Jinshun Bi
AU  - Jianbin Jiao
AU  - Yue Ma
AU  - Baihong Chen
AU  - Yundong Xuan
PY  - 2026
DA  - 2026/09/30
JO  - Micromachines
UR  - https://europepmc.org/article/PMC/PMC13707749
SN  - 2072-666X
ER  -