Memristive synaptic plasticity in Pr0.7Ca0.3MnO 3 RRAM by bio-mimetic programming

N. Panwar, D. Kumar, N. K. Upadhyay, P. Arya, U. Ganguly, B. Rajendran

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

21 Scopus citations

Abstract

Significant efforts are being directed to build new hardware technologies comprising of artificial neurons and synaptic devices that mimic the architecture of the brain for non-Von Neumann computation [1-5]. The computational capability of such networks arises from synaptic devices that can adapt its conductance based on the time of signaling of its two neurons according to rules such as spike timing dependent plasticity (STDP) [6] (Figure 1,2). Prior attempts to develop such synaptic devices have relied on using RRAM devices with current-limiting bipolar diodes. Plasticity was demonstrated by applying complicated waveforms or using complex signaling schemes that require precise clocking [1-5]. By leveraging the intrinsic switching properties of nanoscale Pr0.7Ca0.3MnO3 (PCMO) thin film devices [7-9], we show that (1) very simple programming waveforms that mimic the action potential of biological neurons are sufficient to realize biological plasticity and (2) up-to 64×64 cross-bar arrays of synaptic devices are feasible without any external current-limiting bipolar diodes.

Original languageEnglish (US)
Title of host publication72nd Device Research Conference, DRC 2014 - Conference Digest
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages135-136
Number of pages2
ISBN (Print)9781479954056
DOIs
StatePublished - 2014
Externally publishedYes
Event72nd Device Research Conference, DRC 2014 - Santa Barbara, CA, United States
Duration: Jun 22 2014Jun 25 2014

Publication series

NameDevice Research Conference - Conference Digest, DRC
ISSN (Print)1548-3770

Other

Other72nd Device Research Conference, DRC 2014
Country/TerritoryUnited States
CitySanta Barbara, CA
Period6/22/146/25/14

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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