• DocumentCode
    3084698
  • Title

    Artificial neural network using thin-film transistors - Working confirmation of asymmetric circuit -

  • Author

    Yamaguchi, Yoshio ; Morita, Ryuji ; Fujita, Yoshikazu ; Miyatani, T. ; Kasakawa, Tomohiro ; Kimura, Mizue

  • Author_Institution
    Dept. of Electron. & Inf., Ryukoku Univ., Otsu, Japan
  • fYear
    2013
  • fDate
    5-6 June 2013
  • Firstpage
    78
  • Lastpage
    79
  • Abstract
    We are developing neural networks of device level using thin-film transistors (TFT). By adopting an interconnect-type neural network and utilizing a characteristic shift of poly-Si TFTs as a variable strength of synapse connection, which was originally an issue, we realized the neuron consisting of eight TFTs and synapse of only one TFT. Particularly in this presentation, we confirmed the working by a circuit where the input and output elements are asymmetric. This is a result leading to a super-large, self-learning, and high-flexibility system.
  • Keywords
    elemental semiconductors; logic circuits; neural nets; silicon; thin film circuits; Si; artificial neural networks; asymmetric circuit; characteristic shift; interconnect-type neural network; poly-Si TFT; synapse connection; thin-film transistor; Biological neural networks; Hebbian theory; Inverters; Neurons; Switches; Thin film transistors; asymmetric circuit; neural network; thin-film transistor (TFT);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Future of Electron Devices, Kansai (IMFEDK), 2013 IEEE International Meeting for
  • Conference_Location
    Suita
  • Print_ISBN
    978-1-4673-6106-4
  • Type

    conf

  • DOI
    10.1109/IMFEDK.2013.6602249
  • Filename
    6602249