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Optoelectronic resistive random access memory for neuromorphic vision sensors.

Feichi ZhouZheng ZhouJiewei ChenTsz Hin ChoyJingli WangNing ZhangZiyuan LinShimeng YuJinfeng KangH-S Philip WongYang Chai
Published in: Nature nanotechnology (2019)
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.
Keyphrases
  • working memory
  • deep learning
  • endothelial cells
  • high resolution
  • visible light
  • low cost
  • mass spectrometry
  • health information
  • human health