STiDi-BP: Spike time displacement based error backpropagation in multilayer spiking neural networks
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.11.052
Abstract: Abstract Error backpropagation is the most common approach for direct training of spiking neural networks. However, the non-differentiability of spiking neurons makes the backpropagation of error a challenge. In this paper, we introduce a new… read more here.
Keywords: neural networks; error backpropagation; error; time ... See more keywords
Nonsynaptic Error Backpropagation in Long-Term Cognitive Networks
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2019.2910555
Abstract: We introduce a neural cognitive mapping technique named long-term cognitive network (LTCN) that is able to memorize long-term dependencies between a sequence of input and output vectors, especially in those scenarios that require predicting the… read more here.
Keywords: nonsynaptic error; term; error backpropagation; long term ... See more keywords
Supervised Learning in Multilayer Spiking Neural Networks With Spike Temporal Error Backpropagation.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3164930
Abstract: The brain-inspired spiking neural networks (SNNs) hold the advantages of lower power consumption and powerful computing capability. However, the lack of effective learning algorithms has obstructed the theoretical advance and applications of SNNs. The majority… read more here.
Keywords: neural networks; multilayer; spike temporal; spiking neural ... See more keywords