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Novel Architecture for Cellular Neural Network Suitable for High-Density Integration of Electron Devices-Learning of Multiple Logics

  • Mutsumi KimuraEmail author
  • Yusuke Fujita
  • Tomohiro Kasakawa
  • Tokiyoshi Matsuda
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9489)

Abstract

We will propose a novel architecture for a cellular neural network suitable for high-density integration of electron devices. A neuron consists of only eight transistors, and a synapse consists of just only one transistor. We fabricated a cellular neural network using thin-film devices. Particularly in this time, we confirmed that our neural network can learn multiple logics even in a small-scale neural network. We think that this result indicates that our proposal has a big potential for future electronics using neural networks.

Keywords

Cellular neural network High-density integration Electron device Learning Multiple logics 

Notes

Acknowledgments

We thank Prof. Hakaru Tamukoh of Kyushu Institute of Technology and Prof. Yasuhiko Nakashima of Nara Institute of Science and Technology. This research is partially supported by a research project of the Joint Research Center for Science and Technology at Ryukoku University and grant from the High-Tech Research Center Program for private universities from the Ministry of Education, Culture, Sports, Science and Technology (MEXT).

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Mutsumi Kimura
    • 1
    • 2
    Email author
  • Yusuke Fujita
    • 1
  • Tomohiro Kasakawa
    • 1
  • Tokiyoshi Matsuda
    • 1
  1. 1.Department of Electronics and InformaticsRyukoku UniversityKyotoJapan
  2. 2.Graduate School of Information ScienceNara Institute of Science and TechnologyIkomaJapan

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