Neuromorphic computing technologies will be important for the future of computing, but
much of the work in neuromorphic computing has focused on hardware development. Here …

Though neuromorphic computers have typically targeted applications in machine learning
and neuroscience ('cognitive'applications), they have many computational characteristics …

This work describes the investigation of neuromorphic computing-based spiking neural
network (SNN) models used to filter data from sensor electronics in high energy physics …

Recently, both industry and academia have proposed many different neuromorphic
architectures to execute applications that are designed with Spiking Neural Network (SNN) …

Software simulators play a critical role in the development of new algorithms and system
architectures in any field of engineering. Neuromorphic computing, which has shown …

Neuromorphic computing has many opportunities in future autonomous systems, especially
those that will operate at the edge. However, there are relatively few demonstrations of …

The Abisko project aims to develop an energy-efficient spiking neural network (SNN)
computing architecture and software system capable of autonomous learning and operation …

Neuromorphic computers emulate the human brain while being extremely power efficient for
computing tasks. In fact, they are poised to be critical for energy-efficient computing in the …

Neuromorphic computing has several characteristics that make it an extremely compelling
computing paradigm for post Moore computation. Some of these characteristics include …

Neuromorphic computing is a non-von Neumann computing paradigm that performs
computation by emulating the human brain. Neuromorphic systems are extremely energy …