Magnetic nanoparticles are one of the most important and widely used types of
nanomaterials, whose unique properties make them special compared to other …

Neuromorphic hardware enables fast and power-efficient neural network–based artificial
intelligence that is well suited to solving robotic tasks. Neuromorphic algorithms can be …

Spiking neural networks (SNNs) have garnered increased attention in the field of artificial
general intelligence (AGI) research due to their low power consumption, high computational …

Most memristor-based neural network circuits consider only a single pattern of
overshadowing or emotion, but the relationship between overshadowing and emotion is …

The spiking neural network (SNN) is regarded as a promising candidate to deal with the
great challenges presented by current machine learning techniques, including the high …

Neuromorphic computing is a promising technology that realizes computation based on
event-based spiking neural networks (SNNs). However, fault-tolerant on-chip learning …

This research presents a numerical investigation on the dynamic information of the
axisymmetric sandwich annular sector plate via a higher-order continuum elasticity theory …

Real-time detection of COVID-19 using radiological images has gained priority due to the
increasing demand for fast diagnosis of COVID-19 cases. This paper introduces a novel two …

To investigate the diversified technologies in Internet of Vehicles (IoVs) under intelligent
edge computing, brain-inspired computing techniques are proposed in this study, which is a …

Two-dimensional arrays of bi-component structures made of cobalt and permalloy elliptical
dots with thickness of 25 nm, length 1 mm and width of 225 nm, have been prepared by a …