A Behavioural Compact Model for Programmable Neuromorphic ReRAM

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

Abstract

In this work, we present a compact memristor model for bipolar neuromorphic ReRAM devices. The proposed model focuses on a behavioural high level description of the device, and it reproduces some of the most important characteristics (i.e. conductance, energy dissipation), using the number of pulses as the input variable instead of any electrical. Its functionality is shown by using it to model the behavior of three different ReRAM devices that were fabricated and measured at the CNR-IMM, Agrate Brianza. Considering a train of identical pulses as an input voltage signal consisting of N pulses and where m is the pulse number. The conductance during depression or potentiation can be described.

Details

Original languageEnglish
Title of host publicationProceedings of the 18th ACM International Symposium on Nanoscale Architectures, NANOARCH 2023
PublisherAssociation for Computing Machinery
ISBN (electronic)9798400703256
Publication statusPublished - 18 Dec 2023
Peer-reviewedYes

Publication series

SeriesNanoarch: IEEE/ACM International Symposium on Nanoscale Architectures

Conference

Title18th ACM International Symposium on Nanoscale Architectures
Abbreviated titleNANOARCH 2023
Conference number18
Duration18 - 20 December 2023
Website
LocationTechnische Universität Dresden
CityDresden
CountryGermany

External IDs

ORCID /0000-0001-7436-0103/work/172081488
ORCID /0000-0001-8886-4708/work/172572515

Keywords

Keywords

  • Memristor, Pulse Programming, Pulsed Neural Networks, ReRAM