• DocumentCode
    807
  • Title

    Enhancing Synchronizability of Diffusively Coupled Dynamical Networks: A Survey

  • Author

    Jalili, Mahdi

  • Author_Institution
    Dept. of Comput. Eng., Sharif Univ. of Technol., Tehran, Iran
  • Volume
    24
  • Issue
    7
  • fYear
    2013
  • fDate
    Jul-13
  • Firstpage
    1009
  • Lastpage
    1022
  • Abstract
    In this paper, we review the literature on enhancing synchronizability of diffusively coupled dynamical networks with identical nodes. The last decade has witnessed intensive investigations on the collective behavior over complex networks and synchronization of dynamical systems is the most common form of collective behavior. For many applications, it is desired that the synchronizability-the ability of networks in synchronizing activity of their individual dynamical units-is enhanced. There are a number of methods for improving the synchronization properties of dynamical networks through structural perturbation. In this paper, we survey such methods including adding/removing nodes and/or edges, rewiring the links, and graph weighting. These methods often try to enhance the synchronizability through minimizing the eigenratio of the Laplacian matrix of the connection graph-a synchronizability measure based on the master-stability-function formalism. We also assess the performance of the methods by numerical simulations on a number of real-world networks as well as those generated through models such as preferential attachment, Watts-Strogatz, and Erdos-Rényi.
  • Keywords
    complex networks; eigenvalues and eigenfunctions; graph theory; matrix algebra; network theory (graphs); perturbation techniques; synchronisation; Erdos-Renyi model; Laplacian matrix; Watts-Strogatz model; adding nodes; collective behavior; complex networks; connection graph; diffusively coupled dynamical networks; dynamical systems; eigenratio; graph weighting; identical nodes; individual dynamical units; master-stability-function formalism; numerical simulations; preferential attachment; real-world networks; removing nodes; structural perturbation; synchronizability enhancement; synchronizability measure; synchronization property; synchronizing activity; Complex networks; dynamical systems; synchronizability enhancement; synchronization;
  • fLanguage
    English
  • Journal_Title
    Neural Networks and Learning Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    2162-237X
  • Type

    jour

  • DOI
    10.1109/TNNLS.2013.2250998
  • Filename
    6490063