Applications that generate huge amounts of data in the form of fast streams are becoming
increasingly prevalent, being therefore necessary to learn in an online manner. These …

Artificial neural networks (ANNs) have experienced a rapid advancement for their success in
various application domains, including autonomous driving and drone vision. Researchers …

Biological brains have a natural capacity for resolving certain classification tasks. Studies on
biologically plausible spiking neurons, architectures and mechanisms of artificial neural …

Some neuroscientific studies have demonstrated that the human brain is a complex
integrated spatiotemporal system. The human brain supports a wide range of models …

The brain-inspired spiking neural networks (SNNs) hold the advantages of lower power
consumption and powerful computing capability. However, the lack of effective learning …

Abstract Background and Objective Although existing artificial neural networks have
achieved good results in electroencephalograph (EEG) emotion recognition, further …

There is a biological evidence to prove information is coded through precise timing of spikes
in the brain. However, training a population of spiking neurons in a multilayer network to fire …

This paper presents a new time-varying long-term Synaptic Efficacy Function-based leaky-
integrate-and-fire neuRON model, referred to as SEFRON and its supervised learning rule …

With a similar capability of processing spikes as biological neural systems, networks of
spiking neurons are expected to achieve a performance similar to that of living brains …

The increase in the size of the city and the increase in population mobility have greatly
increased the number of vehicles on the road, and at the same time brought considerable …