Title | ||
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Modeling triplet spike timing dependent plasticity using a hybrid TFT-memristor neuromorphic synapse. |
Abstract | ||
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Triplet-based Spike Timing Dependent Plasticity (TSTDP) is an enhanced synaptic plasticity rule which can be implemented using new nano-scale technologies. Nanocrystalline-silicon thin film transistors (TFT) and memristors are of these nano-scale devices which can be integrated into three-dimensions using low-temperature processing. This paper proposes a new hybrid TFT-memristive circuit that implements the TSTDP. The proposed circuit is composed of two nanoparticle memory-TFTs in series with a current/charge controlled memristor, as the synapse. Our simulation results, using spike pairs with various timing intervals and frequencies, as well as different spike triplets, demonstrate a particularly close match to realistic biological measurements. |
Year | DOI | Venue |
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2019 | 10.1016/j.vlsi.2018.10.004 | Integration |
Keywords | Field | DocType |
Memristor,Nanocrystalline-silicon thin film transistor (TFT),Synapse,Spike-timing-dependent plasticity (STDP) | Synapse,Memristor,Thin-film transistor,Computer science,Neuromorphic engineering,Electronic engineering,Synaptic plasticity,Spike-timing-dependent plasticity | Journal |
Volume | ISSN | Citations |
64 | 0167-9260 | 0 |
PageRank | References | Authors |
0.34 | 6 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Soraya Aghnout | 1 | 0 | 0.34 |
Gholamreza Karimi | 2 | 7 | 4.86 |