Rectified linear postsynaptic potential function for backpropagation in deep spiking neural networks

M Zhang, J Wang, J Wu, A Belatreche… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Spiking neural networks (SNNs) use spatiotemporal spike patterns to represent and transmit
information, which are not only biologically realistic but also suitable for ultralow-power …
被引用次数：172 相关文章

Rectified Linear Postsynaptic Potential Function for Backpropagation in Deep Spiking Neural Networks

M Zhang, J Wang, B Amornpaisannon, Z Zhang… - arXiv preprint arXiv …, 2020 - arxiv.org
Spiking Neural Networks (SNNs) use spatio-temporal spike patterns to represent and
transmit information, which is not only biologically realistic but also suitable for ultra-low …

Rectified Linear Postsynaptic Potential Function for Backpropagation in Deep Spiking Neural Networks

M Zhang, J Wang, B Amornpaisannon… - arXiv e …, 2020 - ui.adsabs.harvard.edu
Abstract Spiking Neural Networks (SNNs) use spatio-temporal spike patterns to represent
and transmit information, which is not only biologically realistic but also suitable for ultra-low …
[PDF] researchgate.net

[PDF][PDF] SPIKE-TIMING-DEPENDENT BACK PROPAGATION IN DEEP SPIKING NEURAL NETWORKS

M Zhang, J Wang, Z Zhang, A Belatreche… - arXiv preprint arXiv …, 2020 - researchgate.net
ABSTRACT The success of Deep Neural Networks (DNNs) can be attributed to its deep
structure, that learns invariant feature representation at multiple levels of abstraction. Brain …

Rectified Linear Postsynaptic Potential Function for Backpropagation in Deep Spiking Neural Networks

M Zhang, J Wang, J Wu, A Belatreche… - … on Neural Networks …, 2022 - nrl.northumbria.ac.uk
Spiking Neural Networks (SNNs) use spatiotemporal spike patterns to represent and
transmit information, which are not only biologically realistic but also suitable for ultralow …

Rectified Linear Postsynaptic Potential Function for Backpropagation in Deep Spiking Neural Networks

M Zhang, J Wang, J Wu… - … on neural networks …, 2022 - pubmed.ncbi.nlm.nih.gov
Spiking neural networks (SNNs) use spatiotemporal spike patterns to represent and transmit
information, which are not only biologically realistic but also suitable for ultralow-power …

Rectified Linear Postsynaptic Potential Function for Backpropagation in Deep Spiking Neural Networks.

M Zhang, J Wang, J Wu, A Belatreche… - IEEE Transactions on …, 2022 - europepmc.org
Spiking neural networks (SNNs) use spatiotemporal spike patterns to represent and transmit
information, which are not only biologically realistic but also suitable for ultralow-power …