• DocumentCode
    179559
  • Title

    Consensus algorithms with state-dependent weights

  • Author

    Sluciak, Ondrej ; Rupp, Markus

  • Author_Institution
    Inst. of Telecommun., Vienna Univ. of Technol., Vienna, Austria
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    5462
  • Lastpage
    5466
  • Abstract
    We provide an analysis of a consensus-type algorithm with weights dependent only on the received data. Differently from previous approaches that require a global knowledge of the network, we consider general weights inferred only from local data which can be modified by local functions on each node. We provide convergence conditions of such algorithms for general weight functions and derive analytical steady states in some selected cases.
  • Keywords
    convergence; distributed algorithms; matrix algebra; sensor fusion; analytical steady states; convergence conditions; distributed consensus-type algorithm; general weight functions; received data; state-dependent weights; Convergence; Markov processes; Network topology; Nickel; Signal processing algorithms; Steady-state; Topology; consensus; convergence; weights;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6854647
  • Filename
    6854647