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

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 …

With the remarkable progress that technology has made, the need for processing data near
the sensors at the edge has increased dramatically. The electronic systems used in these …

We present a hierarchical address-event routing (HiAER) architecture for scalable
communication of neural and synaptic spike events between neuromorphic processors …

This paper presents an extension of the BrainScaleS accelerated analog neuromorphic
hardware model. The scalable neuromorphic architecture is extended by the support for …

This chapter presents the concepts behind the BrainScales (BSS) accelerated analog
neuromorphic computing architecture. It describes the second-generation BrainScales-2 …

The conventional computing method based on the von Neumann architecture is limited by a
series of problems such as high energy consumption, finite data exchange bandwidth …

High-accuracy implementation of biological neural networks is a computationally expensive
task, specially, for large-scale simulations of neuromorphic algorithms. This paper proposes …

In this paper, we propose a Field Programmable Gate Array (FPGA) platform for spike time
dependent encoder and dynamic reservoir in neuromorphic computing processors …

This paper presents a COordinate Rotation DIgital Computer (CORDIC) based Adaptive
Exponential Integrate and Fire (AdEx) neuron for efficient large scale biological neural …