Biologically inspired spiking neural networks are increasingly popular in the field of artificial
intelligence due to their ability to solve complex problems while being power efficient. They …

Spiking neural network (SNN) is a new generation of artificial neural networks (ANNs),
which is more analogous with the brain. It has been widely considered with neural …

Abstract Spiking Neural Network (SNN) is considered more biologically plausible and
energy-efficient on emerging neuromorphic hardware. Recently backpropagation algorithm …

The training of multilayer spiking neural networks (SNNs) using the error backpropagation
algorithm has made significant progress in recent years. Among the various training …

The explosion of “big data” applications imposes severe challenges of speed and scalability
on traditional computer systems. As the performance of traditional Von Neumann machines …

Spiking neural network (SNN), as a brain-inspired energy-efficient neural network, has
attracted the interest of researchers. While the training of spiking neural networks is still an …

Abstract Spiking Neural Networks (SNNs) have recently attracted enormous research
interest since their event-driven and brain-inspired structure enables low-power …

Spiking neural networks (SNNs) significantly reduce energy consumption by replacing
weight multiplications with additions. This makes SNNs suitable for energy-constrained …

Spiking neural network (SNN) is promising but the development has fallen far behind
conventional deep neural networks (DNNs) because of difficult training. To resolve the …

Spiking Neural Networks (SNNs) are a pathway that could potentially empower low-power
event-driven neuromorphic hardware due to their spatio-temporal information processing …