• DocumentCode
    728789
  • Title

    Improvement of learning efficiency in neural network using poly-Si TFTs by synapse TFTs with LDD structure

  • Author

    Morita, Ryohei ; Maeda, Yoshiharu ; Matsuda, Tokiyoshi ; Kimura, Mutsumi

  • Author_Institution
    Dept. of Electron. & Inf., Ryukoku Univ., Otsu, Japan
  • fYear
    2015
  • fDate
    1-4 July 2015
  • Firstpage
    141
  • Lastpage
    142
  • Abstract
    We are developing device-level neural networks using poly-Si TFTs. We succeeded in dramatically reducing the number of transistors in neurons and synapses to integrate a lot of devices, and we also succeeded in actually checking the operation of learning of logics. In this presentation, for the purpose of improvement of learning efficiency, we changed the synapse TFTs from the SD structure to the LDD structure. As a result, we succeeded in improving the learning efficiency by a 5×5 neural network.
  • Keywords
    elemental semiconductors; learning (artificial intelligence); neural nets; silicon; thin film transistors; LDD structure; Si; device-level neural networks; learning efficiency; poly-Si TFT; synapse TFT; Biological neural networks; Degradation; Logic gates; Thin film transistors; Voltage measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Active-Matrix Flatpanel Displays and Devices (AM-FPD), 2015 22nd International Workshop on
  • Conference_Location
    Kyoto
  • Type

    conf

  • DOI
    10.1109/AM-FPD.2015.7173224
  • Filename
    7173224