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 …

Memristors have recently attracted significant interest due to their applicability as promising
building blocks of neuromorphic computing and electronic systems. The dynamic …

In recent years, deep learning has revolutionized the field of machine learning, for computer
vision in particular. In this approach, a deep (multilayer) artificial neural network (ANN) is …

Effective fault diagnosis is a crucial way to reduce the occurrence of severe damages of
many industrial products. With the increasing amount of condition monitoring data, deep …

Next-generation wireless networks must support ultra-reliable, low-latency communication
and intelligently manage a massive number of Internet of Things (IoT) devices in real-time …

Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific
and engineering areas due to its effective learning and reasoning capabilities. The neuro …

The concept that neural information is encoded in the firing rate of neurons has been the
dominant paradigm in neurobiology for many years. This paradigm has also been adopted …

Biological intelligence processes information using impulses or spikes, which makes those
living creatures able to perceive and act in the real world exceptionally well and outperform …

Emotion recognition still poses a challenge lying at the core of the rapidly growing area of
affective computing and is crucial for establishing a successful human–computer interaction …

Abstract Spiking Neuron Networks (SNNs) are often referred to as the 3rd generation of
neural networks. Highly inspired from natural computing in the brain and recent advances in …