Optoelectronic resistive random access memory for neuromorphic vision sensors

Feichi Zhou, Zheng Zhou, Jiewei Chen, Tsz Hin Choy, Jingli Wang, Ning Zhang, Ziyuan Lin, Shimeng Yu, Jinfeng Kang, H. S.Philip Wong, Yang Chai

Research output: Contribution to journalArticlepeer-review

72 Scopus citations

Abstract

Neuromorphic visual systems have considerable potential to emulate basic functions of the human visual system even beyond the visible light region. However, the complex circuitry of artificial visual systems based on conventional image sensors, memory and processing units presents serious challenges in terms of device integration and power consumption. Here we show simple two-terminal optoelectronic resistive random access memory (ORRAM) synaptic devices for an efficient neuromorphic visual system that exhibit non-volatile optical resistive switching and light-tunable synaptic behaviours. The ORRAM arrays enable image sensing and memory functions as well as neuromorphic visual pre-processing with an improved processing efficiency and image recognition rate in the subsequent processing tasks. The proof-of-concept device provides the potential to simplify the circuitry of a neuromorphic visual system and contribute to the development of applications in edge computing and the internet of things.

Original languageEnglish (US)
Pages (from-to)776-782
Number of pages7
JournalNature nanotechnology
Volume14
Issue number8
DOIs
StatePublished - Aug 1 2019

ASJC Scopus subject areas

  • Bioengineering
  • Atomic and Molecular Physics, and Optics
  • Biomedical Engineering
  • Materials Science(all)
  • Condensed Matter Physics
  • Electrical and Electronic Engineering

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