• DocumentCode
    2418866
  • Title

    On contraction analysis of synchronization of neuron networks

  • Author

    Solís-Perales, G. ; Obregón-Pulido, G.

  • Author_Institution
    Dept. de Electron., Univ. de Guadalajara, Guadalajara, Mexico
  • fYear
    2011
  • fDate
    1-4 Oct. 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The synchronization of neuron networks using the contraction theory is reported in this contribution. The contraction theory provides a simple method to determine convergence of trajectories of the systems in the network instead of the Master Stability Function and the calculation of Lyapunov exponents. The objective is to determine the contraction region where once the trajectories reach such region they will converge each other and remain in such a contraction region. Such a condition lies mainly on the system parameters, network topology and coupling strength.
  • Keywords
    Lyapunov methods; network topology; neural nets; stability; Lyapunov exponents; contraction analysis; contraction theory; coupling strength; master stability function; network topology; neuron network synchronization; system parameters; trajectory convergence; Complex networks; Convergence; Couplings; Neurons; Stability analysis; Synchronization; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics Symposium, 2011 IEEE IX Latin American and IEEE Colombian Conference on Automatic Control and Industry Applications (LARC)
  • Conference_Location
    Bogota
  • Print_ISBN
    978-1-4577-1689-8
  • Type

    conf

  • DOI
    10.1109/LARC.2011.6086840
  • Filename
    6086840