Validation of Spiking Neural Networks Using Resistive-Switching Synaptic Device with Spike-Rate-Dependent Plasticity

Author(s):  
Suhyun Bang ◽  
Min-Hye Oh ◽  
Min-Hwi Kim ◽  
Tae-Hyeon Kim ◽  
Dong Keun Lee ◽  
...  
2020 ◽  
Vol 67 (8) ◽  
pp. 3451-3458
Author(s):  
Pavan Kumar Reddy Boppidi ◽  
Bharathwaj Suresh ◽  
Ainur Zhussupbekova ◽  
Pranab Biswas ◽  
Daragh Mullarkey ◽  
...  

2019 ◽  
Vol 213 ◽  
pp. 453-469 ◽  
Author(s):  
W. Wang ◽  
G. Pedretti ◽  
V. Milo ◽  
R. Carboni ◽  
A. Calderoni ◽  
...  

This work addresses the methodology and implementation of a neuromorphic SNN system to compute the temporal information among neural spikes using ReRAM synapses capable of spike-timing dependent plasticity (STDP).


RSC Advances ◽  
2015 ◽  
Vol 5 (119) ◽  
pp. 98110-98117 ◽  
Author(s):  
W. S. Dong ◽  
F. Zeng ◽  
S. H. Lu ◽  
X. J. Li ◽  
C. T. Chang ◽  
...  

Long-term bidirectional frequency selectivity has been achieved in MEH-PPV/PEO–Nd3+cells, which suggests spike-rate-dependent plasticity learning protocol. It depends on pulse shape due to variation of ionic type.


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