Mem-Computing CNNs with Bistable-Like Memristors

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

Contributors

Abstract

In this paper we propose a new mem-computing image processing architecture, called Memristor Cellular Nonlinear Network, which leverages the unique capability of nonvolatile memristors to compute and store data in the same physical nano-scale locations. Adopting a bistable-like memristor in place for the linear resistor in the standard realization of a cell of the nonlinear dynamic array, the resulting network is capable to process information by exploiting the time evolution of the voltages across the memristors as well as to store/retrieve results into/ from the memristances. This attractive feature, absent in a standard Cellular Nonlinear Network, may pave the way towards the future development of a new generation of visual processors with unprecedented spatial resolution.

Details

Original languageEnglish
Title of host publication2019 IEEE International Symposium on Circuits and Systems (ISCAS)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-5
Number of pages5
ISBN (print)978-1-7281-0397-6
Publication statusPublished - 29 May 2019
Peer-reviewedYes

Publication series

SeriesIEEE International Symposium on Circuits and Systems (ISCAS)
ISSN0271-4302

Conference

TitleIEEE International Symposium on Circuits and Systems 2019
Abbreviated titleISCAS 2019
Duration26 - 29 May 2019
Website
Degree of recognitionInternational event
LocationSapporo Convention Center
CitySapporo
CountryJapan

External IDs

Scopus 85066787384
ORCID /0000-0001-7436-0103/work/142240284

Keywords

Keywords

  • Memristors, Computer architecture, Standards, Microprocessors, Threshold voltage, Array signal processing, Nonlinear dynamical systems