Hardware implementations of spiking neurons can be extremely useful for a large variety of
applications, ranging from high-speed modeling of large-scale neural systems to real-time …

We present a mixed-mode analog/digital VLSI device comprising an array of leaky integrate-and-fire
(I&F) neurons, adaptive synapses with spike-timing dependent plasticity, and an …

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

Neurobiological processing systems are remarkable computational devices. They use slow,
stochastic, and inhomogeneous computing elements and yet they outperform today’s most …

Implementing compact, low-power artificial neural processing systems with real-time on-line
learning abilities is still an open challenge. In this paper we present a full-custom mixed-…

We present a low-power analog circuit for implementing a model of a leaky integrate and fire
neuron. Next to being optimized for low-power consumption, the proposed circuit includes …

In this paper we review several ways of realizing asynchronous Spike-Timing-Dependent-Plasticity
(STDP) using memristors as synapses. Our focus is on how to use individual …

Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented as …

Conventional neuro-computing architectures and artificial neural networks have often been
developed with no or loose connections to neuroscience. As a consequence, they have …

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