Integrated photonics arises as a fast and energy-efficient technology for the implementation
of artificial neural networks (ANNs). Indeed, with the growing interest in ANNs, photonics …

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 …

SpiNNaker is a novel chip-based on the ARM processor-which is designed to support large
scale spiking neural networks simulations. In this paper we describe some of the features …

An architecture, systems and methods for a scalable artificial neural network, wherein the
architecture includes: an input layer; at least one hidden layer; an output layer; and a …

The aim of this paper is to propose a new classification approach of artificial neural networks
hardware. Our motivation behind this work is justified by the following two arguments: first …

Digital hardware accelerators are increasingly employed to speed up computation and
reduce power dissipation, enabling real-time operation. Inspired by this paradigm, we …

Abstract Systems and methods for a scalable artificial neural network, wherein the
architecture includes: an input layer; at least one hidden layer; an output layer; and a …

This paper presents a flexible modular rapid prototyping environment for microelectronic
system and circuit designs. The prototyping hardware consists of a PCI bus motherboard …

Neural networks present a fundamentally different model of computation from the
conventional sequential digital model. Modelling large networks on conventional hardware …

In this paper, we present a digital system called (SP/sup 2/INN) for simulating very large-
scale spiking neural networks (VLSNNs) comprising, eg, 1000000 neurons with several …