Reliability of Memristive Devices for High-Performance Neuromorphic Computing: (Invited Paper)
Author:
Affiliation:
1. School of Integrated Circuits, BNRist, Tsinghua University,Beijing Innovation Center for Future Chips,Beijing,China
2. Tsinghua University,Department of Physics,Beijing,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10117589/10117581/10118214.pdf?arnumber=10118214
Reference44 articles.
1. Power-efficient neural network with artificial dendrites
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3. Rotating neurons for all-analog implementation of cyclic reservoir computing
4. An analysis of (the lack of) slip transfer between near-cube oriented grains in pure Al
5. An accelerated analog neuromorphic hardware system emulating NMDA- and calcium-based non-linear dendrites
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