A striking difference between brain-inspired neuromorphic processors and current von
Neumann processor architectures is the way in which memory and processing is organized …

In this study, we present a highly configurable neuromorphic computing substrate and use it
for emulating several types of neural networks. At the heart of this system lies a mixed-signal …

The explosion of “big data” applications imposes severe challenges of speed and scalability
on traditional computer systems. As the performance of traditional Von Neumann machines …

Several analog and digital brain-inspired electronic systems have been recently proposed
as dedicated solutions for fast simulations of spiking neural networks. While these …

Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices,
and models that contrast the pervasive von Neumann computer architecture. This …

Neuromorphic computing covers a diverse range of approaches to information processing
all of which demonstrate some degree of neurobiological inspiration that differentiates them …

Neuromorphic engineering (NE) encompasses a diverse range of approaches to information
processing that are inspired by neurobiological systems, and this feature distinguishes …

Biological neural networks continue to inspire new developments in algorithms and
microelectronic hardware to solve challenging data processing and classification problems …

In this paper, we review some of the novel emerging memory technologies and how they
can enable energy-efficient implementation of large neuromorphic computing systems. We …

No one would accuse neuromorphic computing of lacking ambition. With a mission to
decipher the multitude of secrets nature deploys to achieve unrivalled efficiency and …