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Proceedings Paper

Model selection based on robustness criterion with measurement application
Author(s): Sofiane Brahim-Belhouari; Gilles Fleury; Marie-Eve Davoust
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Paper Abstract

Huber's approach to robust estimation is highly fruitful for solving estimation problems with contaminated data or under incomplete information according to the error structure. A simple selection procedure based on robustness to variations of the errors distribution from the assumed one, is proposed. Minimax M-estimator is used to estimate efficiently the parameters and the measurement quantity. A performance deviation criterion is computed by the mean of the Monte Carlo method improved by the Latin Hypercube Sampling. The selection produced is applied to a real measurement problem, grooves dimensioning using Remote Field Eddy Current inspection.

Paper Details

Date Published: 25 June 1999
PDF: 7 pages
Proc. SPIE 3816, Mathematical Modeling, Bayesian Estimation, and Inverse Problems, (25 June 1999); doi: 10.1117/12.351314
Show Author Affiliations
Sofiane Brahim-Belhouari, Ecole Superieure d'Electricite (France)
Gilles Fleury, Ecole Superieure d'Electricite (France)
Marie-Eve Davoust, Ecole Superieure d'Electricite (France)


Published in SPIE Proceedings Vol. 3816:
Mathematical Modeling, Bayesian Estimation, and Inverse Problems
Françoise J. Prêteux; Ali Mohammad-Djafari; Edward R. Dougherty, Editor(s)

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