Implementation of hardware-based neural network using memristors with abrupt SET and gradual RESET characteristics

Yeon Pyo, Sahn Nahm, Jichai Jeong, Jaeyoung Shin

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

Abstract

Recent advance of artificial intelligence comes from the rapid growth of artificial neural network technology. Memristors play a crucial role in the hardware implementation of artificial neural networks, thanks to the multilevel conductance of memristors by switching behaviors. Here, we propose a synaptic device with a Pr0.7Ca0.3MnO3 (PCMO) switching layer which shows the abrupt SET and gradual RESET switching characteristics. Improved linearity of the synaptic transmission caused by switching characteristics can enhance the classification performance of neuromorphic systems.

Original languageEnglish
Title of host publication8th International Winter Conference on Brain-Computer Interface, BCI 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728147079
DOIs
Publication statusPublished - 2020 Feb
Event8th International Winter Conference on Brain-Computer Interface, BCI 2020 - Gangwon, Korea, Republic of
Duration: 2020 Feb 262020 Feb 28

Publication series

Name8th International Winter Conference on Brain-Computer Interface, BCI 2020

Conference

Conference8th International Winter Conference on Brain-Computer Interface, BCI 2020
CountryKorea, Republic of
CityGangwon
Period20/2/2620/2/28

Keywords

  • memristor
  • neural network
  • neuromorphic system
  • synapse

ASJC Scopus subject areas

  • Behavioral Neuroscience
  • Cognitive Neuroscience
  • Artificial Intelligence
  • Human-Computer Interaction

Cite this

Pyo, Y., Nahm, S., Jeong, J., & Shin, J. (2020). Implementation of hardware-based neural network using memristors with abrupt SET and gradual RESET characteristics. In 8th International Winter Conference on Brain-Computer Interface, BCI 2020 [9061641] (8th International Winter Conference on Brain-Computer Interface, BCI 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BCI48061.2020.9061641