Results 131 to 140 of about 3,555,912 (299)
Advanced Materials, EarlyView.Two‐dimensional Ag11 and Ag12 cluster‐assembled materials (CAMs) are synthesized, offering atomically precise platforms with tunable electronic properties. The resulting materials exhibit robust memristive switching and neuromorphic response, demonstrating their promise for advanced nanoelectronic and memory applications.
Noohul Alam +7 more
wiley +1 more source
Spiking Neural Network For Energy Efficient Learning And Recognition [PDF]
, 2020 Nowadays, people are confronted with an increasingly large amount of data and a tremendous change of human-machine interaction modes. It is a challenging and time-consuming task for traditional computing system to deal with the content of information ...
Wong, Yan Chiew, Wang, Ning Lo
core +2 more sources
A Survey on Spiking Neural Networks
INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS, 2021 Chan Sik Han, Keon Myung Lee
openaire +2 more sources
Whetstone Trained Spiking Deep Neural Networks to Spiking Neural Networks [PDF]
, 2019 A deep neural network is a non-spiking artificial neural network which uses multiple structured layers to extract features from the input. Spiking neural networks are another type of artificial neural network which closely mimic biology with time ...
Zhao, Jiajia
core
Volatile Memristive Devices With Tunable Temporal Dynamics For Event‐Based Sensing
Advanced Materials, EarlyView.Tunable volatile memristive devices can serve various neural‐inspired tasks that require different time windows of information retention. The ionic‐based volatility of the presented Pt/a‐STO/TaOx/Ta device stack can be reproducibly and controllably tuned in multiple ways.
Dimitrios Spithouris +7 more
wiley +1 more source
Bioengineered Interfaces for Peripheral Nerve Sensory Restoration
Advanced Materials, EarlyView.Half of amputees abandon their prosthetics for lack of feeling. This review charts the full path from peripheral nerve injury to restored sensation, through surgical, regenerative, noninvasive, and implanted approaches, and shows how injury type and interface material properties determine which strategy can deliver naturalistic feedback, and why ...
Sydney Swedick +4 more
wiley +1 more source
Scalable network emulation on analog neuromorphic hardware
Frontiers in NeuroscienceWe present a novel software feature for the BrainScaleS-2 accelerated neuromorphic platform that facilitates the partitioned emulation of large-scale spiking neural networks.
Elias Arnold +6 more
doaj +1 more source
The chronotron: a neuron that learns to fire temporally-precise spike patterns [PDF]
, 2010 In many cases, neurons process information carried by the precise timing of spikes. Here we show how neurons can learn to generate specific temporally-precise output spikes in response to input spike patterns, thus processing and memorizing information ...
Răzvan V. Florian
core
A communication infrastructure for a million processor machine
, 2010 SpiNNaker (Spiking Neural Network architecture) is a massively parallel computing machine, comprising a million ARM9 cores. These are realised on 50000 chips, 20 cores/chip. While it could be classed as a MIMD machine, there is no unifying bus structure,
Brown, Andrew D. +7 more
core +2 more sources
Advanced Materials, EarlyView.Organic artificial neurons couple mechanical deformation and ionic environments through nonlinear mechano‐electrochemical dynamics. Mechanical strain and electrolyte concentration reshape their nonlinear electrical characteristics, programming excitatory or inhibitory spiking responses that mimic mechanosensitive biological neurons and enable ...
Rassen Boukraa +4 more
wiley +1 more source