Academic Journal
Exploiting Bias Temperature Instability for Reservoir Computing in Edge Artificial Intelligence Applications ...
| العنوان: | Exploiting Bias Temperature Instability for Reservoir Computing in Edge Artificial Intelligence Applications ... |
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| المؤلفون: | IEEE International Symposium on Reliability Physics 2024, Bury, Erik, Degraeve, Robin, Franco, Jacopo, Guo, Yuanyang, Kaczer, Ben, Saraza-Canflanca, Pablo, Vandemaele, Michiel, Verbauwhede, Ingrid |
| بيانات النشر: | Underline Science Inc. |
| سنة النشر: | 2024 |
| المجموعة: | DataCite Metadata Store (German National Library of Science and Technology) |
| مصطلحات موضوعية: | Reliability Physics |
| الوصف: | We show that thanks to the existence of NBTI, pFETs can be used to build a physical reservoir. We demonstrate this using the Compact-Physical (Comphy) framework for BTI modeling and substantiate it with a gait and voice authentication example. Subsequently, a hardware demonstration reveals that only 9 pFETs are sufficient to distinguish gait signals from different subjects. Notably, this implementation obviates the need for specialized device engineering, allowing for direct utilization of CMOS technology. ... |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | unknown |
| Relation: | https://dx.doi.org/10.1109/IRPS48228.2024.10529383 |
| DOI: | 10.48448/jqpx-xq25 |
| الاتاحة: | https://dx.doi.org/10.48448/jqpx-xq25 https://underline.io/lecture/96065-exploiting-bias-temperature-instability-for-reservoir-computing-in-edge-artificial-intelligence-applications |
| رقم الانضمام: | edsbas.DE92B9A9 |
| قاعدة البيانات: | BASE |
| DOI: | 10.48448/jqpx-xq25 |
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