MAP-SNN: Mapping spike activities with multiplicity, adaptability, and plasticity into bio-plausible spiking neural networks

Spiking Neural Networks (SNNs) are considered more biologically realistic and power-efficient as they imitate the fundamental mechanism of the human brain. Backpropagation (BP) based SNN learning algorithms that utilize deep learning frameworks have achieved good performance. However, those BP-based...

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Detalles Bibliográficos
Autores principales: Yu, Chengting, Du, Yangkai, Chen, Mufeng, Wang, Aili, Wang, Gaoang, Li, Erping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531034/
https://www.ncbi.nlm.nih.gov/pubmed/36203801
http://dx.doi.org/10.3389/fnins.2022.945037

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531034/
https://www.ncbi.nlm.nih.gov/pubmed/36203801
http://dx.doi.org/10.3389/fnins.2022.945037

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