STDP and STDP variations with memristors for spiking neuromorphic learning systems

T Serrano-Gotarredona, T Masquelier… - Frontiers in …, 2013‏ - frontiersin.org
In this paper we review several ways of realizing asynchronous Spike-Timing-Dependent-
Plasticity (STDP) using memristors as synapses. Our focus is on how to use individual …

A review of current neuromorphic approaches for vision, auditory, and olfactory sensors

A Vanarse, A Osseiran, A Rassau - Frontiers in neuroscience, 2016‏ - frontiersin.org
Conventional vision, auditory, and olfactory sensors generate large volumes of redundant
data and as a result tend to consume excessive power. To address these shortcomings …

Optoelectronic synapse based on igzo‐alkylated graphene oxide hybrid structure

J Sun, S Oh, Y Choi, S Seo, MJ Oh… - Advanced Functional …, 2018‏ - Wiley Online Library
Recently, research interest in brain‐inspired neuromorphic computing based on robust and
intelligent artificial neural networks has surged owing to the ability of such technology to …

Memory and information processing in neuromorphic systems

G Indiveri, SC Liu - Proceedings of the IEEE, 2015‏ - ieeexplore.ieee.org
A striking difference between brain-inspired neuromorphic processors and current von
Neumann processor architectures is the way in which memory and processing is organized …

2D electric-double-layer phototransistor for photoelectronic and spatiotemporal hybrid neuromorphic integration

J Jiang, W Hu, D **e, J Yang, J He, Y Gao, Q Wan - Nanoscale, 2019‏ - pubs.rsc.org
The hardware implementation of neuromorphic computing has attracted growing interest as
a promising candidate for confronting the bottleneck of traditional von Neumann computers …

Pattern recognition using carbon nanotube synaptic transistors with an adjustable weight update protocol

S Kim, B Choi, M Lim, J Yoon, J Lee, HD Kim, SJ Choi - ACS nano, 2017‏ - ACS Publications
Recent electronic applications require an efficient computing system that can perform data
processing with limited energy consumption. Inspired by the massive parallelism of the …

Neuromorphic electronic circuits for building autonomous cognitive systems

E Chicca, F Stefanini, C Bartolozzi… - Proceedings of the …, 2014‏ - ieeexplore.ieee.org
Several analog and digital brain-inspired electronic systems have been recently proposed
as dedicated solutions for fast simulations of spiking neural networks. While these …

A synergistic future for AI and ecology

BA Han, KR Varshney, S LaDeau… - Proceedings of the …, 2023‏ - pnas.org
Research in both ecology and AI strives for predictive understanding of complex systems,
where nonlinearities arise from multidimensional interactions and feedbacks across multiple …

Integration of nanoscale memristor synapses in neuromorphic computing architectures

G Indiveri, B Linares-Barranco, R Legenstein… - …, 2013‏ - iopscience.iop.org
Conventional neuro-computing architectures and artificial neural networks have often been
developed with no or loose connections to neuroscience. As a consequence, they have …

Hire-snn: Harnessing the inherent robustness of energy-efficient deep spiking neural networks by training with crafted input noise

S Kundu, M Pedram, PA Beerel - Proceedings of the IEEE …, 2021‏ - openaccess.thecvf.com
Low-latency deep spiking neural networks (SNNs) have become a promising alternative to
conventional artificial neural networks (ANNs) because of their potential for increased …