When it comes to tech, most don't think too much about how things like NPUs and GPUs work. But the differences between them ...

Networks are systems comprised of two or more connected devices, biological organisms or other components, which typically ...

Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn ...

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks ...

Spiking Neural Networks (SNNs) are a cutting-edge approach to artificial intelligence, designed to emulate the brain's architecture and functionality. Their ...

The AI revolution is bringing with it a whole new vocabulary to describe its advances. Use this glossary to stay up-to-date.

With increase in the applications of autonomous systems, in both civilian and military domains, it has become increasingly important to provide formal ...

Abstract: This brief proposes a neural network-enhanced digital background calibration scheme for calibrating the linear and the third-order nonlinear gain errors of the residue amplifier (RA) in ...

Abstract: The range-spread target detection problem typically faces uncertainty in the number and locations of target scattering centers (TSCs), which severely limits the performance of traditional ...

The growing ubiquity of artificial intelligence (AI) in applications is rapidly changing everyday life, underscoring the need to understand its social intelligence. A new AI study examines the social ...