Self-organization of an inhomogeneous memristive hardware for sequence learning
One gap between the neuro-inspired computing and its applications lies in the intrinsic variability of the devices. Here, Payvand et al. suggest a technologically plausible co-design of the hardware architecture which takes into account and exploits the physics behind memristors.
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-10-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-022-33476-6 |