Memristor-Based In-Circuit Computation for Trace-Based STDP

Wang, DeyuFudan Univ, Sch Informat Sci & Technol, State Key Lab ASIC & Syst, Shanghai, Peoples R China. (author)

QC 20221111Part of proceedings: ISBN 978-1-6654-0996-4
Recently, memristors have been widely used to implement Spiking Neural Networks (SNNs), which is promising in edge computing scenarios. However, most memristor-based SNN implementations adopt simplified spike-timing-dependent plasticity (STDP) for the online learning process. It is challenging for memristor-based implementations to support the trace-based STDP learning rules that have been widely used in neuromorphic applications. This paper proposed a versatile memristor-based architecture to implement the synaptic-level trace-based STDP learning rules. Especially, the similarity between synaptic trace dynamics and the memristor nonlinearity is explored and exploited to emulate the trace variables of trace-based STDP. As two typical trace-based STDP learning rules, the pairwise STDP and the triplet STDP, are simulated on two typical nonlinear bipolar memristor devices. The simulation results show that the behavior of physical memristor devices can be well estimated (below 6% in terms of the relative root-mean-square error), and the memristor-based in-circuit computation for trace-based STDP learning rules can achieve a high correlation coefficient over 98%.

Xu, JiaweiFudan Univ, Sch Informat Sci & Technol, State Key Lab ASIC & Syst, Shanghai, Peoples R China. (author)
Li, FengFudan Univ, Sch Informat Sci & Technol, State Key Lab ASIC & Syst, Shanghai, Peoples R China. (author)
Zhang, LianhaoTech Univ Denmark, Dept Elect Engn, Lyngby, Denmark. (author)
Wang, YuningUniv Turku, Dept Future Technol, Turku, Finland. (author)
Lansner, Anders,Professor,1949-KTH,Beräkningsvetenskap och beräkningsteknik (CST)(Swepub:kth)u12s8cr8 (author)
Hemani, Ahmed,1961-KTH,Elektronik och inbyggda system(Swepub:kth)u131a9ju (author)
Zheng, Li-RongFudan Univ, Sch Informat Sci & Technol, State Key Lab ASIC & Syst, Shanghai, Peoples R China. (author)
Zou, ZhuoFudan Univ, Sch Informat Sci & Technol, State Key Lab ASIC & Syst, Shanghai, Peoples R China. (author)
Fudan Univ, Sch Informat Sci & Technol, State Key Lab ASIC & Syst, Shanghai, Peoples R China.Tech Univ Denmark, Dept Elect Engn, Lyngby, Denmark. (creator_code:org_t)

In:2022 Ieee International Conference On Artificial Intelligence Circuits And Systems (Aicas 2022): Institute of Electrical and Electronics Engineers (IEEE), s. 1-4

By the author/editor: Wang, Deyu; Xu, Jiawei; Li, Feng; Zhang, Lianhao; Wang, Yuning; Lansner, Anders, ...; show more...; Hemani, Ahmed, 1 ...; Zheng, Li-Rong; Zou, Zhuo; show less...

About the subject

NATURAL SCIENCES: NATURAL SCIENCES; and Computer and Inf ...; and Bioinformatics

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