Deep neural networks with rate-based neurons have exhibited tremendous progress in the
last decade. However, the same level of progress has not been observed in research on …

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

This paper presents a new learning algorithm developed for a three layered spiking neural
network for pattern classification problems. The learning algorithm maximizes the interclass …

In recent years, classification problems have been widely studied as one of the critical
research directions in artificial intelligence. Efficiently simulating the human brain's ability to …

This paper presents a meta-neuron learning-based spiking neural classifier with a time-
varying weight model (MeST). MeST is developed to handle the class imbalance in …

This paper proposes a new personalised prognostic/diagnostic system that supports
classification, prediction and pattern recognition when both static and dynamic …

Understanding consumer preference for products or services is important for users
(individuals, platforms, merchants, and so forth) to make decisions. However, the preference …

In this article, we developed an approach for detecting brain regions that contribute to
Alzheimer's disease (AD) using support vector machine (SVM) classifiers and the recently …

Algorithms designed for addressing typical supervised classification problems can only
learn from a fixed set of samples and labels, making them unsuitable for the real world …

A brain-computer interface (BCI) is both a hardware and software based communication
system that allows cerebral activity to control computers or external devices. The …