Artificial neural networks have been used as a powerful processing tool in various areas
such as pattern recognition, control, robotics, and bioinformatics. Their wide applicability has …

As a new brain-inspired computational model of the artificial neural network, a spiking
neural network encodes and processes neural information through precisely timed spike …

We introduce a supervised learning algorithm for multilayer spiking neural networks. The
algorithm overcomes a limitation of existing learning algorithms: it can be applied to neurons …

A novel online learning algorithm for Spiking Neural Networks (SNNs) with dynamically
adaptive structure is presented. The main contribution of this work lies in the fact that the …

Recent research has shown the potential capability of spiking neural networks (SNNs) to
model complex information processing in the brain. There is biological evidence to prove the …

Over the last decade, various spiking neural network models have been proposed, along
with a similarly increasing interest in spiking models of computation in computational …

Breast cancer is a serious disease across the world, and it is one of the largest causes of
cancer death for women. The traditional diagnosis is not only time consuming but also easily …

This article presents a novel network, contribution-degree-based spiking neural network
(CDSNN), which combines ideas of spiking neural network (SNN) and fuzzy set theory. In …

Spiking Neural Networks (SNN) are third generation neural networks and are considered to
be the most biologically plausible so far. As a relative newcomer to the field of artificial …

Spikes are an important part of information transmission between neurons in the biological
brain. Biological evidence shows that information is carried in the timing of individual action …