Flexible artificial vision computing system based on FeOx optomemristor for speech recognition

  • Jie Li
  • , Yue Xin
  • , Bai Sun
  • , Dengshun Gu
  • , Changrong Liao
  • , Xiaofang Hu
  • , Lidan Wang
  • , Shukai Duan
  • , Guangdong Zhou

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

With the advancement of artificial intelligence, optic in-sensing reservoir computing based on emerging semiconductor devices is high desirable for real-time analog signal processing. Here, we disclose a flexible optomemristor based on C27H30O15/FeOx heterostructure that presents a highly sensitive to the light stimuli and artificial optic synaptic features such as short- and long-term plasticity (STP and LTP), enabling the developed optomemristor to implement complex analogy signal processing through building a real-physical dynamic-based in-sensing reservoir computing algorithm and yielding an accuracy of 94.88% for speech recognition. The charge trapping and detrapping mediated by the optic active layer of C27H30O15 that is extracted from the lotus flower is response for the positive photoconductance memory in the prepared optomemristor. This work provides a feasible organic−inorganic heterostructure as well as an optic in-sensing vision computing for an advanced optic computing system in future complex signal processing.

Original languageEnglish
Article number012604
JournalJournal of Semiconductors
Volume46
Issue number1
DOIs
StatePublished - 1 Jan 2025

Keywords

  • analogy signal processing
  • flexible optomemristor
  • optic computing
  • reservoir computing

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