• DocumentCode
    1838016
  • Title

    CNN using memristors for neighborhood connections

  • Author

    Lehtonen, E. ; Laiho, M.

  • Author_Institution
    Dept. of Inf. Technol., Univ. of Turku, Turku, Finland
  • fYear
    2010
  • fDate
    3-5 Feb. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper we consider using memristors to implement the neighborhood connections of a CNN. First the benefits and drawbacks of using memristors as programmable CNN weights are described. Then, an existing memristor model is improved to allow full-scale simulation of the design. The new model is implemented in the SPICE simulation environment and is not restricted to CNN applications. Then, the CNN cell design is presented and simulations describing memristor programming are performed.
  • Keywords
    cellular neural nets; logic design; memristors; CNN cell design; CNN neighborhood connections; SPICE simulation environment; cellular neural networks; memristor programming; programmable CNN weights; Analog memory; Cellular networks; Cellular neural networks; Circuits; Information technology; Memristors; Neural networks; SPICE; Virtual manufacturing; Voltage; CNN cell; Cellular nonlinear neural networks; Memristor; Model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Nanoscale Networks and Their Applications (CNNA), 2010 12th International Workshop on
  • Conference_Location
    Berkeley, CA
  • Print_ISBN
    978-1-4244-6679-5
  • Type

    conf

  • DOI
    10.1109/CNNA.2010.5430304
  • Filename
    5430304