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Linear leaky-integrate-and-fire neuron model based spiking neural networks and its mapping relationship to deep neural networks
Spiking neural networks (SNNs) are brain-inspired machine learning algorithms with merits such as biological plausibility and unsupervised learning capability. Previous works have shown that converting Artificial Neural Networks (ANNs) into SNNs is a practical and efficient approach for implementing...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Frontiers Media S.A.
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9448910/ https://www.ncbi.nlm.nih.gov/pubmed/36090262 http://dx.doi.org/10.3389/fnins.2022.857513 |