Parameter-Bounding Algorithms for Linear Errors-in-Variables Models

  • S. M. Veres
  • J. P. Norton

Abstract

Computational techniques are considered for the errors-in-variables (EIV) problem with bounds specified on the errors in all variables. The significant difference in difficulty in bounding the parameters of a dynamic EIV model, compared with the static case, is explained. Conditions for the feasible set of the parameters to be the union of polytopes are discussed, and a search technique to find the nonlinear bounds for the dynamic EIV problem is described. A simulation example compares EIV and equation-error bounding. Techniques for shortening the computation of EIV parameter bounds, and for finding polytope and ellipsoid approximations, are given.

Keywords

Nonlinear Bound Uncertain Variable Parameter Bound Sampling Instant Ellipsoid Approximation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • S. M. Veres
    • 1
  • J. P. Norton
    • 1
  1. 1.School of Electronic and Electrical EngineeringUniversity of BirminghamEdgbaston, BirminghamUK

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