• DocumentCode
    2480877
  • Title

    The Configurable Digital Cellular Neural - Hopfield Network

  • Author

    Zeffer, Tamas ; Hidvegi, Timot

  • Author_Institution
    Fac. of Inf. Technol., Peter Pazmany Catholic Univ., Budapest
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    160
  • Lastpage
    164
  • Abstract
    A configurable artificial neuron network that is capable of establishing both the emulated digital cellular neural network (CNN) and the Hopfield network is described. The configurable neural network is designed with the method of modularity where each module is a three weighted input neuron. The network can be optionally large limited only by the gate number available on a chip. Also, the network is reconfigurable during operation
  • Keywords
    Hopfield neural nets; cellular neural nets; neural chips; Hopfield network; configurable artificial neuron network; emulated digital cellular neural network; gate number; modularity method; neural chip; Arithmetic; Artificial neural networks; Cellular networks; Cellular neural networks; Equations; Hopfield neural networks; Information technology; Neural networks; Neurons; Strontium;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Engineering Systems, 2006. INES '06. Proceedings. International Conference on
  • Conference_Location
    London
  • Print_ISBN
    0-7803-9708-8
  • Type

    conf

  • DOI
    10.1109/INES.2006.1689361
  • Filename
    1689361