• DocumentCode
    696242
  • Title

    Estimating the interconnection structure of dynamical networks

  • Author

    Blackhall, Lachlan ; Rotkowitz, Michael

  • Author_Institution
    Res. Sch. of Inf. Sci. & Eng., Australian Nat. Univ., Canberra, ACT, Australia
  • fYear
    2009
  • fDate
    23-26 Aug. 2009
  • Firstpage
    2954
  • Lastpage
    2959
  • Abstract
    Complex dynamical networks emerge from the physical or information based interconnection of many dynamical systems. These networks display emergent behaviour that is best understood through knowledge of the interconnection structure of the network. We analyze and compare a variety of existing regression techniques (some sparsity inducing and other not) with a recursive sparse estimator, presented recently by the authors, for determining this interconnection structure. In large networks the ability to recursively estimate the interconnection structure of the network may be advantageous for a number of reasons and thus this work represents a proof-of-concept that such an approach is feasible. Results comparing existing and recursive sparse regression techniques for determining the interconnection structure of a simple complex dynamical network are presented.
  • Keywords
    graph theory; matrix algebra; regression analysis; complex dynamical networks; interconnection graph; interconnection structure estimation; recursive sparse estimator; recursive sparse regression technique; regression techniques; Communities; Estimation; Europe; Least squares approximations; Linear regression; Network topology; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 2009 European
  • Conference_Location
    Budapest
  • Print_ISBN
    978-3-9524173-9-3
  • Type

    conf

  • Filename
    7074857