Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/113147
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dc.contributor.authorNouri, M.-
dc.contributor.authorJalilian, M.-
dc.contributor.authorHayati, M.-
dc.contributor.authorAbbott, D.-
dc.date.issued2018-
dc.identifier.citationIEEE Transactions on Circuits and Systems, Part 2: Express Briefs, 2018; 65(6):804-808-
dc.identifier.issn1549-7747-
dc.identifier.issn1558-3791-
dc.identifier.urihttp://hdl.handle.net/2440/113147-
dc.description.abstractSpike 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.-
dc.description.statementofresponsibilityMoslem Nouri, Maisam Jalilian, Mohsen Hayati, Derek Abbott-
dc.language.isoen-
dc.publisherIEEE-
dc.rights© 2017 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.-
dc.source.urihttp://dx.doi.org/10.1109/tcsii.2017.2750214-
dc.subjectPiecewise 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)-
dc.titleA digital neuromorphic realization of pair-based and triplet-based spike-timing-dependent synaptic plasticity-
dc.typeJournal article-
dc.identifier.doi10.1109/TCSII.2017.2750214-
pubs.publication-statusPublished-
dc.identifier.orcidAbbott, D. [0000-0002-0945-2674]-
Appears in Collections:Aurora harvest 3
Electrical and Electronic Engineering publications

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