반도체디스플레이기술학회지 (Journal of the Semiconductor & Display Technology)

한국반도체디스플레이기술학회 (The Korean Society Of Semiconductor & Display Technology)
권호 표지

IGZO 멤리스터 소자기반 뉴로모픽 컴퓨팅 정확도 향상

Improved Accuracy in Neuromorphic Computing Based on IGZO Memristor Devices

  • 최서진 (상명대학교 시스템반도체공학과) ;
  • 민경진 (상명대학교 시스템반도체공학과) ;
  • 이종환 (상명대학교 시스템반도체공학과)
  • Seojin Choi (Department of System Semiconductor Engineering, Sangmyung University) ;
  • Kyoungjin Min (Department of System Semiconductor Engineering, Sangmyung University) ;
  • Jonghwan Lee (Department of System Semiconductor Engineering, Sangmyung University)
  • 투고 : 2023.12.05
  • 심사 : 2023.12.19
  • 발행 : 2023.12.31
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초록

This paper presents the synaptic characteristics of IGZO memristors in neuromorphic computing, using MATLAB/Simulink and NeuroSim. In order to investigate the variations in the conductivity of IGZO memristor and the corresponding changes in the hidden layer, simulations are conducted by using the MNIST dataset. It was observed from simulation results that the recognition accuracy could be dependent on various parameters of IGZO memristor, along with the experimental exploration. Moreover, we identified optimal parameters to achieve high accuracy, showing an outstanding accuracy of 96.83% in image classification.

키워드

과제정보

This work is funded by a 2023 research Grant from Sangmyung University.

참고문헌

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