ANP-R: A 22nm 0.88pJ/SOP Asynchronous SNN-based Processor with Coarse-Grained Reconfigurable Architecture Enabling Multisensory On-chip Incremental Learning for Edge AI.
- DOI
- 10.1109/tbcas.2026.3708212
- Published
- 2026 Jun 29
- Container
- IEEE transactions on biomedical circuits and systems
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tbcas.2026.3708212,
title = {ANP-R: A 22nm 0.88pJ/SOP Asynchronous SNN-based Processor with Coarse-Grained Reconfigurable Architecture Enabling Multisensory On-chip Incremental Learning for Edge AI.},
author = {Cheng Z and Huo D and Zhang J and Wang Z and Chen H},
year = {2026},
journal = {IEEE transactions on biomedical circuits and systems},
doi = {10.1109/tbcas.2026.3708212},
url = {https://doi.org/10.1109/tbcas.2026.3708212}
}RIS
TY - JOUR TI - ANP-R: A 22nm 0.88pJ/SOP Asynchronous SNN-based Processor with Coarse-Grained Reconfigurable Architecture Enabling Multisensory On-chip Incremental Learning for Edge AI. AU - Cheng Z AU - Huo D AU - Zhang J AU - Wang Z AU - Chen H PY - 2026 JO - IEEE transactions on biomedical circuits and systems DO - 10.1109/tbcas.2026.3708212 UR - https://doi.org/10.1109/tbcas.2026.3708212 ER -
APA
Z, C., D, H., J, Z., Z, W., & H, C. (2026). ANP-R: A 22nm 0.88pJ/SOP Asynchronous SNN-based Processor with Coarse-Grained Reconfigurable Architecture Enabling Multisensory On-chip Incremental Learning for Edge AI.. IEEE transactions on biomedical circuits and systems. https://doi.org/10.1109/tbcas.2026.3708212
Source records
- pubmed · retrieved 2026-11-10T14:53:26.882Z