Neuro-inspired electronic skin for robots

F Liu, S Deswal, A Christou, Y Sandamirskaya… - Science robotics, 2022 - science.org
Touch is a complex sensing modality owing to large number of receptors (mechano, thermal,
pain) nonuniformly embedded in the soft skin all over the body. These receptors can gather …

A comprehensive review on emerging artificial neuromorphic devices

J Zhu, T Zhang, Y Yang, R Huang - Applied Physics Reviews, 2020 - pubs.aip.org
The rapid development of information technology has led to urgent requirements for high
efficiency and ultralow power consumption. In the past few decades, neuromorphic …

An artificial spiking afferent nerve based on Mott memristors for neurorobotics

X Zhang, Y Zhuo, Q Luo, Z Wu, R Midya, Z Wang… - Nature …, 2020 - nature.com
Neuromorphic computing based on spikes offers great potential in highly efficient computing
paradigms. Recently, several hardware implementations of spiking neural networks based …

A review of artificial spiking neuron devices for neural processing and sensing

JK Han, SY Yun, SW Lee, JM Yu… - Advanced Functional …, 2022 - Wiley Online Library
A spiking neural network (SNN) inspired by the structure and principles of the human brain
can significantly enhance the energy efficiency of artificial intelligence computing by …

Biological plausibility and stochasticity in scalable VO2 active memristor neurons

W Yi, KK Tsang, SK Lam, X Bai, JA Crowell… - Nature …, 2018 - nature.com
Neuromorphic networks of artificial neurons and synapses can solve computationally hard
problems with energy efficiencies unattainable for von Neumann architectures. For image …

Emerging memory devices for neuromorphic computing

NK Upadhyay, H Jiang, Z Wang… - Advanced Materials …, 2019 - Wiley Online Library
A neuromorphic computing system may be able to learn and perform a task on its own by
interacting with its surroundings. Combining such a chip with complementary metal–oxide …

Chaotic dynamics in nanoscale NbO2 Mott memristors for analogue computing

S Kumar, JP Strachan, RS Williams - Nature, 2017 - nature.com
At present, machine learning systems use simplified neuron models that lack the rich
nonlinear phenomena observed in biological systems, which display spatio-temporal …

Emerging neuromorphic devices

D Ielmini, S Ambrogio - Nanotechnology, 2019 - iopscience.iop.org
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 …

A novel true random number generator based on a stochastic diffusive memristor

H Jiang, D Belkin, SE Savel'ev, S Lin, Z Wang… - Nature …, 2017 - nature.com
The intrinsic variability of switching behavior in memristors has been a major obstacle to
their adoption as the next generation of universal memory. On the other hand, this natural …

Towards oxide electronics: a roadmap

M Coll, J Fontcuberta, M Althammer, M Bibes… - Applied surface …, 2019 - orbit.dtu.dk
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 …