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 …
[HTML][HTML] Coupled oscillators for computing: A review and perspective
Coupled oscillators are highly complex dynamical systems, and it is an intriguing concept to
use this oscillator dynamics for computation. The idea is not new, but is currently the subject …
use this oscillator dynamics for computation. The idea is not new, but is currently the subject …
[HTML][HTML] Neuromorphic computing with multi-memristive synapses
Neuromorphic computing has emerged as a promising avenue towards building the next
generation of intelligent computing systems. It has been proposed that memristive devices …
generation of intelligent computing systems. It has been proposed that memristive devices …
[HTML][HTML] Unsupervised learning of digit recognition using spike-timing-dependent plasticity
In order to understand how the mammalian neocortex is performing computations, two
things are necessary; we need to have a good understanding of the available neuronal …
things are necessary; we need to have a good understanding of the available neuronal …
Neuromemristive circuits for edge computing: A review
O Krestinskaya, AP James… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
The volume, veracity, variability, and velocity of data produced from the ever increasing
network of sensors connected to Internet pose challenges for power management …
network of sensors connected to Internet pose challenges for power management …
Synaptic electronics: materials, devices and applications
In this paper, the recent progress of synaptic electronics is reviewed. The basics of biological
synaptic plasticity and learning are described. The material properties and electrical …
synaptic plasticity and learning are described. The material properties and electrical …
[HTML][HTML] Pattern classification by memristive crossbar circuits using ex situ and in situ training
Memristors are memory resistors that promise the efficient implementation of synaptic
weights in artificial neural networks. Whereas demonstrations of the synaptic operation of …
weights in artificial neural networks. Whereas demonstrations of the synaptic operation of …
Spin-transfer torque magnetic memory as a stochastic memristive synapse for neuromorphic systems
AF Vincent, J Larroque, N Locatelli… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Spin-transfer torque magnetic memory (STT-MRAM) is currently under intense academic
and industrial development, since it features non-volatility, high write and read speed and …
and industrial development, since it features non-volatility, high write and read speed and …
[HTML][HTML] 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 …
Plasticity (STDP) using memristors as synapses. Our focus is on how to use individual …
Materials and devices as solutions to computational problems in machine learning
The growth of machine learning, combined with the approaching limits of conventional
digital computing, are driving a search for alternative and complementary forms of …
digital computing, are driving a search for alternative and complementary forms of …