Memristor-based synapses and neurons for neuromorphic computing

Le Zheng, Sangho Shin, Sung Mo Steve Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

A memristor-based architecture for neuromorphic computing is proposed. With memristors mimicking key characteristics of synapses and neurons, such nanoscale neural networks exhibit learning and memory effects with high integration density and scalability. Simulations demonstrate important features including adjustable spike generation, spike-timing and spike-rate dependent plasticity.

Original languageEnglish (US)
Title of host publication2015 IEEE International Symposium on Circuits and Systems, ISCAS 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1150-1153
Number of pages4
ISBN (Electronic)9781479983919
DOIs
StatePublished - Jul 27 2015
Externally publishedYes
EventIEEE International Symposium on Circuits and Systems, ISCAS 2015 - Lisbon, Portugal
Duration: May 24 2015May 27 2015

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2015-July
ISSN (Print)0271-4310

Other

OtherIEEE International Symposium on Circuits and Systems, ISCAS 2015
Country/TerritoryPortugal
CityLisbon
Period5/24/155/27/15

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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