Brain-inspired computing, drawing inspiration from the fundamental structure and
information-processing mechanisms of the human brain, has gained significant momentum …

The potential of neuromorphic computing to bring about revolutionary advancements in
multiple disciplines, such as artificial intelligence (AI), robotics, neurology, and cognitive …

Human activity recognition (HAR) is a classification problem involving time-dependent
signals produced by body monitoring, and its application domain covers all the aspects of …

Brain-inspired computing, which is inspired by the information processing procedure and the
biophysiological structure of the brain, is believed to have the potential to drive the next …

Neuromorphic computing utilizes spiking neural networks (SNNs) to offer power/energy-
efficient solutions for complex machine-learning problems in hardware. However, neural …

In recent years, with the development of artificial intelligence chip, brain-like computing chip
has become one of the hotspots in the field of artificial intelligence chip. Brain-like computing …

Brain-inspired computing uses the law of brain processing information to simulate the brain.
The network formed by the transmission of different signals between neurons has the ability …

Brain-inspired computing uses the information processing method of human brain to
process unstructured information in real time. It is an important way to artificial general …

Neuromorphic technologies have the potential to revolutionize cognitive computing by
accelerating biologically inspired learning algorithms. These algorithms and architectures …

Context-dependent learning allows the network model to learn and adjust autonomously
according to the environment. SNN allows the network to run at high speed and low power …