Learning rules in spiking neural networks: A survey

Z Yi, J Lian, Q Liu, H Zhu, D Liang, J Liu - Neurocomputing, 2023 - Elsevier
Spiking neural networks (SNNs) are a promising energy-efficient alternative to artificial
neural networks (ANNs) due to their rich dynamics, capability to process spatiotemporal …
被引用次数：25 相关文章
[PDF] researchgate.net

[PDF][PDF] Learning Rules in Spiking Neural Networks: A Survey

Z Yia, J Lianb, Q Liuc, H Zhud, D Liange, J Liua - researchgate.net
Spiking neural networks (SNNs) are a promising energy-efficient alternative to artificial
neural networks (ANNs) due to their rich dynamics, capability to process spatiotemporal …

Learning rules in spiking neural networks: A survey

Z Yi, J Lian, Q Liu, H Zhu, D Liang, J Liu - 2023 - ir.lzu.edu.cn
摘要Spiking neural networks (SNNs) are a promising energy-efficient alternative to artificial
neural networks (ANNs) due to their rich dynamics, capability to process spatiotemporal …

Learning rules in spiking neural networks:: A survey

Z Yi, J Lian, Q Liu, H Zhu, D Liang, J Liu - 2023 - dl.acm.org
Spiking neural networks (SNNs) are a promising energy-efficient alternative to artificial
neural networks (ANNs) due to their rich dynamics, capability to process spatiotemporal …