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)


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.


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



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).


  1. 1.
    Chua, L.O., Yang, L.: Cellular neural networks: theory. IEEE Trans. Circ. Syst. 32, 1257––1272 (1988)MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    Koeppl, H., Chua, L.O.: An adaptive cellular non-linear network and its application. In: 2007 International Symposium on Nonlinear Theory and Its Applications (NOLTA 2007), pp. 15–––18 (2007)Google Scholar
  3. 3.
    Crounse, K.R., Chua, L.O., Thiran, P., Setti, G.: Characterization and dynamics of pattern formation in cellular neural networks. Int. J. Bifurcat. Chaos 6, 1703–––1724 (1996)CrossRefzbMATHGoogle Scholar
  4. 4.
    Morie, T., Miyake, M., Nagata, M., Iwata, A.: A 1-D CMOS PWM cellular neural network circuit and resistive-fuse network operation. In: 2001 International Conference on Solid State Devices and Materials (SSDM 2001), pp. 90–––91 (2001)Google Scholar
  5. 5.
    Kasakawa, T., Tabata, H., Onodera, R., Kojima, H., Kimura, M., Hara, H., Inoue, S.: An artificial neural network at device level using simplified architecture and thin-film transistors. IEEE Trans. Electron Devices 57, 2744–––2750 (2010)CrossRefGoogle Scholar
  6. 6.
    Kimura, M., Miyatani, T., Fujita, Y., Kasakawa, T.: Apoptotic self-organized electronic device using thin-film transistors for artificial neural networks with unsupervised learning functions. Jpn. J. Appl. Phys. 54, 03CB02 (2015)CrossRefGoogle Scholar
  7. 7.
    Hebb, D.O.: The Organization of Behavior. Wiley, London (1949)Google Scholar
  8. 8.
    Kasakawa, T., Tabata, H., Onodera, R., Kojima, H., Kimura, M., Hara, H., Inoue, S.: Degradation evaluation of poly-Si TFTs by comparing normal and reverse characteristics and behavior analysis of hot-carrier degradation. Solid-State Electron. 56, 207–––210 (2011)CrossRefGoogle Scholar
  9. 9.
    Kaneda, T., Hirose, D., Miyasako, T., Tue, P.T., Murakami, Y., Kohara, S., Li, J., Mitani, T., Tokumitsu, E., Shimoda, T.: Rheology printing for metal-oxide patterns and devices. J. Mater. Chem. C 2, 40–––49 (2014)CrossRefGoogle Scholar
  10. 10.
    Kaltenbrunner, M., Sekitani, T., Reeder, J., Yokota, T., Kuribara, K., Tokuhara, T., Drack, M., Schwoediauer, R., Graz, I., Bauer-Gogonea, S., Bauer, S., Someya, T.: An ultra-lightweight design for imperceptible plastic electronics. Nature 499, 458–––463 (2013)CrossRefGoogle Scholar
  11. 11.
    Sameshima, T., Usui, S., Sekiya, M.: XeCl excimer laser annealing used in the fabrication of poly-Si TFT’s. IEEE Electron Device Lett. 7, 276–––278 (1986)CrossRefGoogle Scholar

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

Personalised recommendations