Towards spike-based machine intelligence with neuromorphic computing
Guided by brain-like 'spiking'computational frameworks, neuromorphic computing—brain-
inspired computing for machine intelligence—promises to realize artificial intelligence while …
inspired computing for machine intelligence—promises to realize artificial intelligence while …
Neuromorphic computing using non-volatile memory
Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path
for implementing massively-parallel and highly energy-efficient neuromorphic computing …
for implementing massively-parallel and highly energy-efficient neuromorphic computing …
The future of memristors: Materials engineering and neural networks
K Sun, J Chen, X Yan - Advanced Functional Materials, 2021 - Wiley Online Library
Abstract From Deep Blue to AlphaGo, artificial intelligence and machine learning are
booming, and neural networks have become the hot research direction. However, due to the …
booming, and neural networks have become the hot research direction. However, due to the …
STDP-based spiking deep convolutional neural networks for object recognition
Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in
spiking neural networks (SNN) to extract visual features of low or intermediate complexity in …
spiking neural networks (SNN) to extract visual features of low or intermediate complexity in …
Memory and information processing in neuromorphic systems
A striking difference between brain-inspired neuromorphic processors and current von
Neumann processor architectures is the way in which memory and processing is organized …
Neumann processor architectures is the way in which memory and processing is organized …
Electrochemical‐Memristor‐Based Artificial Neurons and Synapses—Fundamentals, Applications, and Challenges
Artificial neurons and synapses are considered essential for the progress of the future brain‐
inspired computing, based on beyond von Neumann architectures. Here, a discussion on …
inspired computing, based on beyond von Neumann architectures. Here, a discussion on …
Learning without neurons in physical systems
Learning is traditionally studied in biological or computational systems. The power of
learning frameworks in solving hard inverse problems provides an appealing case for the …
learning frameworks in solving hard inverse problems provides an appealing case for the …
Emerging neuromorphic devices
Artificial intelligence (AI) has the ability of revolutionizing our lives and society in a radical
way, by enabling machine learning in the industry, business, health, transportation, and …
way, by enabling machine learning in the industry, business, health, transportation, and …
Spintronic nanodevices for bioinspired computing
Bioinspired hardware holds the promise of low-energy, intelligent, and highly adaptable
computing systems. Applications span from automatic classification for big data …
computing systems. Applications span from automatic classification for big data …
Towards oxide electronics: a roadmap
At the end of a rush lasting over half a century, in which CMOS technology has been
experiencing a constant and breathtaking increase of device speed and density, Moore's …
experiencing a constant and breathtaking increase of device speed and density, Moore's …