A design methodology for fault-tolerant computing using astrocyte neural networks-Reference-Cited by-同舟云学术

A design methodology for fault-tolerant computing using astrocyte neural networks

Published:2022-05-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 19th ACM International Conference on Computing Frontiers
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Author:

Isik Murat¹,Paul Ankita¹,Varshika M. Lakshmi¹,Das Anup¹

Affiliation:

1. Drexel University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3528416.3530232

Reference20 articles.

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2. A. Balaji , " Mapping spiking neural networks to neuromorphic hardware," TVLSI , 2020 . A. Balaji et al., "Mapping spiking neural networks to neuromorphic hardware," TVLSI, 2020.

3. Y. Cao , " Spiking deep convolutional neural networks for energy-efficient object recognition," IJCV , 2015 . Y. Cao et al., "Spiking deep convolutional neural networks for energy-efficient object recognition," IJCV, 2015.

4. P. K. Huynh , " Implementing spiking neural networks on neuromorphic architectures: A review," arXiv , 2022 . P. K. Huynh et al., "Implementing spiking neural networks on neuromorphic architectures: A review," arXiv, 2022.

5. S. Moradi , " A scalable multicore architecture with heterogeneous memory structures for dynamic neuromorphic asynchronous processors (DYNAPs)," TBCAS , 2017 . S. Moradi et al., "A scalable multicore architecture with heterogeneous memory structures for dynamic neuromorphic asynchronous processors (DYNAPs)," TBCAS, 2017.

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