Generation of STDP With Non-Volatile Tunnel-FET Memory for Large-Scale and Low-Power Spiking Neural Networks

Spiking neural networks (SNNs) have attracted considerable attention as next-generation neural networks. As SNNs consist of devices that have spike-timing-dependent plasticity (STDP) characteristics, STDP is one of the critical characteristics we need to consider to implement an SNN. In this study,...

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Veröffentlicht in:IEEE journal of the Electron Devices Society 2020, Vol.8, p.1266-1271
Hauptverfasser: Kino, Hisashi, Fukushima, Takafumi, Tanaka, Tetsu
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Sprache:eng
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Zusammenfassung:Spiking neural networks (SNNs) have attracted considerable attention as next-generation neural networks. As SNNs consist of devices that have spike-timing-dependent plasticity (STDP) characteristics, STDP is one of the critical characteristics we need to consider to implement an SNN. In this study, we generated the STDP of a biological synapse with non-volatile tunnel-field-effect-transistor (tunnel FET) memory that has a charge-storage layer and a tunnel FET structure. Tunnel FET is a promising structure to reduce the operation voltage owing to its steep sub-threshold slope. Therefore, the non-volatile tunnel-FET memory we propose enables the implementation of low-operation-voltage SNNs. This article reports the {I-V} , programming, and both symmetric and asymmetric STDP characteristics of a non-volatile tunnel-FET memory with p-channel-MOS-like operation.
ISSN:2168-6734
2168-6734
DOI:10.1109/JEDS.2020.3025336