Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/113147
Citations
Scopus Web of Science® Altmetric
?
?
Type: Journal article
Title: A digital neuromorphic realization of pair-based and triplet-based spike-timing-dependent synaptic plasticity
Author: Nouri, M.
Jalilian, M.
Hayati, M.
Abbott, D.
Citation: IEEE Transactions on Circuits and Systems II: Express Briefs, 2018; 65(6):804-808
Publisher: IEEE
Issue Date: 2018
ISSN: 1549-7747
1558-3791
Statement of
Responsibility: 
Moslem Nouri, Maisam Jalilian, Mohsen Hayati, Derek Abbott
Abstract: Spike timing dependent plasticity is one of the synaptic plasticity rules that plays a key role in brain learning. This brief presents a set of piecewise linear approximations in order to produce a digital neuromorphic realization of the pair-based and triplet-based spike timing dependent plasticity rules. The proposed models are validated by simulation and an field-programmable gate array implementation demonstrates how the proposed approximations can alter synaptic weights according to the timing differences between a set of different patterns of spikes.
Keywords: Piecewise linear approximation; field programmable gate array (FPGA); spiking neural network (SNN); synaptic learning rule; pair-based spike-timing-dependent synaptic plasticity (PSTDP); triplet-based spike-timing-dependent synaptic plasticity (TSTDP)
Rights: © 2017 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
RMID: 0030090514
DOI: 10.1109/TCSII.2017.2750214
Appears in Collections:Electrical and Electronic Engineering publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.