• DocumentCode
    718567
  • Title

    The research of memristor-based neural network components operation accuracy in control and communication systems

  • Author

    Danilin, S.N. ; Shchanikov, S.A. ; Galushkin, A.I.

  • Author_Institution
    Murom Inst., Vladimir State Univ., Murom, Russia
  • fYear
    2015
  • fDate
    21-23 May 2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This research is aimed to create a general approach to developing methods and algorithms designed for defining and providing memristor-based artificial neural network (ANNM) components operation accuracy in control and communication systems. Here we list factors which affect the operation accuracy of memristors usied as the synapses in the ANNM. We have created Simscape models of memristor neurons and ANNM for investigating the influence of these factors on the ANNM accuracy. This article presents the results of the initial phase of our research.
  • Keywords
    control systems; memristor circuits; neurocontrollers; ANNM components operation accuracy; Simscape models; communication system; control system; memristor neurons; memristor-based artificial neural network components operation accuracy; Accuracy; Algorithm design and analysis; Artificial neural networks; Computational modeling; Memristors; Neurons; Solid modeling; artificial neural network; control and communication systems; memristive systems; memristor; neurocomputers; operation accuracy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Communications (SIBCON), 2015 International Siberian Conference on
  • Conference_Location
    Omsk
  • Print_ISBN
    978-1-4799-7102-2
  • Type

    conf

  • DOI
    10.1109/SIBCON.2015.7147034
  • Filename
    7147034