• DocumentCode
    3091358
  • Title

    Distributed Bayesian parameter estimation

  • Author

    Hoballah, I.Y. ; Varshney, P.K.

  • Author_Institution
    Syracuse University, Syracuse, New York
  • Volume
    26
  • fYear
    1987
  • fDate
    9-11 Dec. 1987
  • Firstpage
    2223
  • Lastpage
    2228
  • Abstract
    This paper considers the problem of distributed Bayesian parameter estimation. Three commonly used cost criteria namely mean square error, absolute error and uniform cost are employed. Optimum estimation rules at the individual sensors and optimum combining rule are obtained. Suboptimum solutions when the combining rule is restricted to be a linear one are also derived. A simple example is presented for illustration.
  • Keywords
    Bayesian methods; Costs; Density functional theory; Estimation theory; Mean square error methods; Parameter estimation; Signal processing; State estimation; Vectors; Yield estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1987. 26th IEEE Conference on
  • Conference_Location
    Los Angeles, California, USA
  • Type

    conf

  • DOI
    10.1109/CDC.1987.272937
  • Filename
    4049702
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3091358