• DocumentCode
    714227
  • Title

    Observer-based synchronization of networked Hindmarsh-Rose neurons

  • Author

    Bayat, F. Kemal ; Yilmaz, Mutlu ; El-Hawary, M.E.

  • Author_Institution
    Dept. of Electr. & Electron., Marmara Univ., Istanbul, Turkey
  • fYear
    2015
  • fDate
    3-6 May 2015
  • Firstpage
    1605
  • Lastpage
    1611
  • Abstract
    The main objective of this paper is to develop an observer-based synchronization scheme for networked Hindmarsh-Rose neuron models. Regarding synchronization as a state estimation problem, an observer design approach is used for estimating full state dynamics. Stability of the trajectories to be synchronized is determined by utilization of the contraction theory that provides an efficient tool for analyzing convergence of manifolds with respect to each other. Thereupon, a region where contraction of trajectories takes place is determined; therefore the corresponding error dynamics of the model remain in that contracting region. Consequent results are also supported by a numerical simulation example in the end demonstrating the effectiveness of our approach.
  • Keywords
    networked control systems; neurocontrollers; nonlinear control systems; observers; stability; synchronisation; contraction theory; error dynamics; full state dynamics estimation; manifold convergence analysis; networked Hindmarsh-Rose neuron models; nonlinear systems; numerical simulation; observer design approach; observer-based synchronization scheme; state estimation problem; trajectory stability; Convergence; Couplings; Jacobian matrices; Neurons; Observers; Stability analysis; Synchronization; Contraction theory; Hindmarsh-Rose neuron model; Nonlinear systems; Observers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering (CCECE), 2015 IEEE 28th Canadian Conference on
  • Conference_Location
    Halifax, NS
  • ISSN
    0840-7789
  • Print_ISBN
    978-1-4799-5827-6
  • Type

    conf

  • DOI
    10.1109/CCECE.2015.7129521
  • Filename
    7129521