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SPICE Study of STDP Characteristics in a Drift and Diffusive Memristor-Based Synapse for Neuromorphic Computing

Authors
Hu, SumanKang, JaehyunKim, TaeyoonLee, SuyounPark, Jong KeukKim, InhoKim, JaewookKwak, Joon YoungPark, JongkilKim, Gyu-TaeChoi, ShinhyunJeong, Yeonjoo
Issue Date
2022
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Memristors; Synapses; Immune system; Neurons; SPICE; Shape; Biological system modeling; Ca-2+; drift memristor; diffusive memristor; hump; STDP; SPICE simulation; voltage division
Citation
IEEE ACCESS, v.10, pp.6381 - 6392
Indexed
SCIE
SCOPUS
Journal Title
IEEE ACCESS
Volume
10
Start Page
6381
End Page
6392
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/137589
DOI
10.1109/ACCESS.2022.3140476
ISSN
2169-3536
Abstract
Neuromorphic hardware is a system with massive potential to enable efficient computing by mimicking the human brain. The novel system processes information using neuron spikes (Action Potentials) and the synaptic connections between neurons are trained using biologically plausible methods like spike-timing-dependent plasticity (STDP). Memristor is one of the promising candidates to implement such neuromorphic hardware. Two types of memristors, diffusive and drift, have been proposed to form a synapse showing faithful emulation of STDP, where the diffusion effect is used to trace the spike timing history crucial for STDP and the drift memristor keeps the weight information in a longer time scale. The purpose of this paper is to systematically investigate STDP characteristics in such a synapse with serially connected two memristors using SPICE models. The results show that STDP properties are strongly dependent on device parameters and even the shape of STDP curves is modified. Different shapes of the STDP curve were identified. The results and analysis could support the design of emerging device-based synapses, which can faithfully mimic biological STDP characteristics for future neuromorphic systems.
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공과대학 (전기전자공학부)
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