• DocumentCode
    819932
  • Title

    Minimax and L_{1} curve fitting in non-Gaussian MAP estimation

  • Author

    Scott, Peter D.

  • Author_Institution
    State University of New York, Buffalo, NY, USA
  • Volume
    20
  • Issue
    5
  • fYear
    1975
  • fDate
    10/1/1975 12:00:00 AM
  • Firstpage
    690
  • Lastpage
    691
  • Abstract
    A class of non-Gaussian estimation problems is equivalent to minimax and L1curve fitting. The curve fit is shown to be algebraically dual to optimization of a positive semidefinite quadratic form with linear inequalities, which is solved by a fast quadratic program based on Graves´ simplex algorithm. An example compares the performance of this estimator with the (suboptimal) minimum mean-squared error (MMSE) estimations generated by quadratic curve fitting.
  • Keywords
    Curve fitting; Least-squares estimation; Linear systems, stochastic discrete-time; Minimax estimation; Optimization methods; State estimation; Covariance matrix; Curve fitting; Laplace equations; Minimax techniques; Probability density function; Quadratic programming; Random variables; Statistics; White noise; Zinc;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.1975.1101080
  • Filename
    1101080
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=819932