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A low cost neuromorphic learning engine based on a high performance supervised SNN learning algorithm
Spiking neural networks (SNNs) are more energy- and resource-efficient than artificial neural networks (ANNs). However, supervised SNN learning is a challenging task due to non-differentiability of spikes and computation of complex terms. Moreover, the design of SNN learning engines is not an easy t...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113267/ https://www.ncbi.nlm.nih.gov/pubmed/37072443 http://dx.doi.org/10.1038/s41598-023-32120-7 |