• DocumentCode
    702384
  • Title

    Data validation in the presence of imprecisely known correlations

  • Author

    Hanebeck, U.D. ; Horn, J.

  • Author_Institution
    Inst. of Computer Design and Fault Tolerance, Universität Karlsruhe, 76128 Karlsruhe, Germany
  • fYear
    2003
  • fDate
    1-4 Sept. 2003
  • Firstpage
    2631
  • Lastpage
    2636
  • Abstract
    This paper derives fundamental results for data validation in the presence of imprecisely known correlations. Given a constraint on the maximum absolute correlation of a given estimate and measurement data, a tight upper bound for the joint covariance matrix is derived, which finally yields a modified Mahalanobis distance. The special cases of one-dimensional and two-dimensional random variables are discussed.
  • Keywords
    Correlation; Covariance matrices; Ellipsoids; Joints; Measurement uncertainty; Random variables; Upper bound; Covariance Bounds; Data Validation; Imprecisely Known Correlations; Mahalanobis Distance; Stochastic Uncertainties;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    European Control Conference (ECC), 2003
  • Conference_Location
    Cambridge, UK
  • Print_ISBN
    978-3-9524173-7-9
  • Type

    conf

  • Filename
    7086438
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=702384