The stochastic modeling of TiO2 memristor and its usage in neuromorphic system design

Miao Hu, Yu Wang, Qinru Qiu, Yiran Chen, Hai Li

Research output: Chapter in Book/Entry/PoemConference contribution

33 Scopus citations

Abstract

Memristor, the fourth basic circuit element, has shown great potential in neuromorphic circuit design for its unique synapse-like feature. However, though the continuous resistance state of memristor has been expected, obtaining and maintaining an arbitrary intermediate state cannot be well controlled in nowadays memristive system. In addition, the stochastic switching behaviors have been widely observed. To facilitate the investigation on memristor-based hardware implementation, we built a stochastic behavior model of TiO2 memristive devices based on the real experimental results. By leveraging the stochastic behavior of memristors, a macro cell design composed of multiple parallel connecting memristors can be successfully used in implementing the weight storage unit and the stochastic neuron - the two fundamental components in neural network (NN)s, providing a feasible solution in memristor-based hardware implementation.

Original languageEnglish (US)
Title of host publication2014 19th Asia and South Pacific Design Automation Conference, ASP-DAC 2014 - Proceedings
Pages831-836
Number of pages6
DOIs
StatePublished - 2014
Event2014 19th Asia and South Pacific Design Automation Conference, ASP-DAC 2014 - Suntec, Singapore
Duration: Jan 20 2014Jan 23 2014

Publication series

NameProceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC

Other

Other2014 19th Asia and South Pacific Design Automation Conference, ASP-DAC 2014
Country/TerritorySingapore
CitySuntec
Period1/20/141/23/14

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering

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