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 …

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 …

While Moore's law has driven exponential computing power expectations, its nearing end
calls for new avenues for improving the overall system performance. One of these avenues …

The goal of neuromorphic engineering is to build electronic systems that mimic the ability of
the brain to perform fuzzy, fault-tolerant, and stochastic computation, without sacrificing …

Neuromorphic computing was originally referred to as the hardware that mimics neuro-
biological architectures to implement models of neural systems. The concept was then …

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

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 …

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

Brain-inspired computing is an emerging field, which aims to reach brainlike performance in
real-time processing of sensory data. The challenges that need to be addressed toward …

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