Plasticity in memristive devices for spiking neural networks
Memristive devices present a new device technology allowing for the realization of compact
non-volatile memories. Some of them are already in the process of industrialization …
non-volatile memories. Some of them are already in the process of industrialization …
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 …
Engineering incremental resistive switching in TaO x based memristors for brain-inspired computing
Brain-inspired neuromorphic computing is expected to revolutionize the architecture of
conventional digital computers and lead to a new generation of powerful computing …
conventional digital computers and lead to a new generation of powerful computing …
Immunity to device variations in a spiking neural network with memristive nanodevices
Memristive nanodevices can feature a compact multilevel nonvolatile memory function, but
are prone to device variability. We propose a novel neural network-based computing …
are prone to device variability. We propose a novel neural network-based computing …
Visual pattern extraction using energy-efficient “2-PCM synapse” neuromorphic architecture
We introduce a novel energy-efficient methodology “2-PCM Synapse” to use phase-change
memory (PCM) as synapses in large-scale neuromorphic systems. Our spiking neural …
memory (PCM) as synapses in large-scale neuromorphic systems. Our spiking neural …
Extraction of temporally correlated features from dynamic vision sensors with spike-timing-dependent plasticity
O Bichler, D Querlioz, SJ Thorpe, JP Bourgoin… - Neural networks, 2012 - Elsevier
A biologically inspired approach to learning temporally correlated patterns from a spiking
silicon retina is presented. Spikes are generated from the retina in response to relative …
silicon retina is presented. Spikes are generated from the retina in response to relative …
Bioinspired programming of memory devices for implementing an inference engine
Cognitive tasks are essential for the modern applications of electronics, and rely on the
capability to perform inference. The Von Neumann bottleneck is an important issue for such …
capability to perform inference. The Von Neumann bottleneck is an important issue for such …
Physical aspects of low power synapses based on phase change memory devices
In this work, we demonstrate how phase change memory (PCM) devices can be used to
emulate biologically inspired synaptic functions in particular, potentiation and depression …
emulate biologically inspired synaptic functions in particular, potentiation and depression …
Model of neuromorphic odorant-recognition network
We propose a new model for a neuromorphic olfactory analyzer based on memristive
synapses. The model comprises a layer of receptive neurons that perceive various odors …
synapses. The model comprises a layer of receptive neurons that perceive various odors …
On-chip training spiking neural networks using approximated backpropagation with analog synaptic devices
Hardware-based spiking neural networks (SNNs) inspired by a biological nervous system
are regarded as an innovative computing system with very low power consumption and …
are regarded as an innovative computing system with very low power consumption and …