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

A Memristor Model with Concise Window Function for Spiking Brain-Inspired Computation

  • Article/chapterEnglish2021

Publisher, publication year, extent ...

  • Institute of Electrical and Electronics Engineers (IEEE),2021
  • printrdacarrier

Numbers

  • LIBRIS-ID:oai:DiVA.org:kth-306472
  • https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-306472URI
  • https://doi.org/10.1109/AICAS51828.2021.9458424DOI

Supplementary language notes

  • Language:English
  • Summary in:English

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  • Subject category:ref swepub-contenttype
  • Subject category:kon swepub-publicationtype

Notes

  • Part of ISBN 978-1-6654-1913-0QC 20220216
  • This paper proposes a concise window function to build a memristor model, simulating the widely-observed non-linear dopant drift phenomenon of the memristor. Exploiting the non-linearity, the memristor model is applied to the in-situ neuromorphic solution for a cortex-inspired spiking neural network (SNN), spike-based Bayesian Confidence Propagation Neural Network (BCPNN). The improved memristor model utilizing the proposed window function is able to retain the boundary effect and resolve the boundary lock and inflexibility problem, while it is simple in form that can facilitate large-scale neuromorphic model simulation. Compared with the state-of-the-art general memristor model, the proposed memristor model can achieve a 5.8x reduction of simulation time at a competitive fitting level in cortex-comparable large-scale software simulation. The evaluation results show an explicit similarity between the non-linear dopant drift phenomenon of the memristor and the BCPNN learning rule, and the memristor model is able to emulate the key traces of BCPNN with a correlation coefficient over 0.99.

Subject headings and genre

Added entries (persons, corporate bodies, meetings, titles ...)

  • Wang, DeyuFudan 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)
  • Stathis, DimitriosKTH,Elektronik och inbyggda system(Swepub:kth)u1dyeh7b (author)
  • Yang, YuKTH,Elektronik och inbyggda system(Swepub:kth)u13v3htk (author)
  • Jin, YiFudan Univ, Sch Informat Sci & Technol, State Key Lab ASIC & Syst, Shanghai, Peoples R China. (author)
  • Lansner, Anders,ProfessorKTH,Beräkningsvetenskap och beräkningsteknik (CST)(Swepub:kth)u12s8cr8 (author)
  • Hemani, Ahmed,1961-KTH,Elektronik och inbyggda system(Swepub:kth)u131a9ju (author)
  • Zou, ZhuoFudan Univ, Sch Informat Sci & Technol, State Key Lab ASIC & Syst, Shanghai, Peoples R China.(Swepub:kth)u1muelo7 (author)
  • Zheng, Li-RongFudan 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)

Related titles

  • In:3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS: Institute of Electrical and Electronics Engineers (IEEE)

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