• DocumentCode
    2024528
  • Title

    Using Exponential Mixture Models for Suboptimal Distributed Data Fusion

  • Author

    Julier, Simon J. ; Bailey, Tim ; Uhlmann, Jeffrey K.

  • Author_Institution
    Department of Computer Science, University College London, Malet Place, London WC1E 6BT, UK. S.Julier@cs.ucl.ac.uk
  • fYear
    2006
  • fDate
    13-15 Sept. 2006
  • Firstpage
    160
  • Lastpage
    163
  • Abstract
    In this paper we investigate the use of Exponential Mixture Densities (EMDs) as suboptimal update rules for distributed data fusion. We show that EMDs have a pointwise bound "from below" on the minimum value of the probability distribution. However, the distributions are not bounded from above and thus can be interpreted as a fusion operation.
  • Keywords
    Computer science; Data engineering; Educational institutions; History; Network topology; Robots; Robustness; Sensor fusion; State estimation; Yield estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nonlinear Statistical Signal Processing Workshop, 2006 IEEE
  • Conference_Location
    Cambridge, UK
  • Print_ISBN
    978-1-4244-0581-7
  • Electronic_ISBN
    978-1-4244-0581-7
  • Type

    conf

  • DOI
    10.1109/NSSPW.2006.4378844
  • Filename
    4378844
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2024528