• DocumentCode
    2184490
  • Title

    Minimum variance estimation with uncertain statistical model

  • Author

    Calafiore, Giuseppe ; Ghaoui, Laurent El

  • Author_Institution
    Dipt. di Autom. e Inf., Politecnico di Torino, Italy
  • Volume
    4
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    3497
  • Abstract
    We consider the problem of parameter estimation in a linear stochastic model, where the observations are affected by noise with uncertain variance. In particular, we discuss a linear estimator which minimizes a worst-case measure of the a-posteriori covariance of the parameters. The estimate is efficiently computed by means of convex programming, and may be updated with upcoming observations in a recursive setting
  • Keywords
    convex programming; linear systems; minimax techniques; parameter estimation; stochastic systems; uncertain systems; convex programming; covariance uncertainty; linear systems; minimax technique; minimum variance estimation; optimization; parameter estimation; stochastic systems; uncertain statistical model; Covariance matrix; Gaussian noise; Minimax techniques; Noise measurement; Parameter estimation; Particle measurements; Recursive estimation; Robustness; Stochastic resonance; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-7061-9
  • Type

    conf

  • DOI
    10.1109/.2001.980400
  • Filename
    980400
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2184490