Model selection via worst-case criterion for nonlinear bounded-error estimation

Author

Brahim-Belhouari, Sofiane ; Kieffer, Michel ; Fleury, Gilles ; Jaulin, Luc ; Walter, Eric

Author_Institution

Ecole Superieure d´´Electr., Gif-sur-Yvette, France

Volume

2

fYear

1999

fDate

1999

Firstpage

1075

Abstract

In this paper the problem of model selection for measurement purposes is studied. A new selection procedure in a deterministic framework is proposed. The problem of nonlinear bounded-error estimation is viewed as a set inversion procedure. As each candidate model structure leads to a specific set of admissible values of the measurement vector the worst-case criterion is used to select the optimal model. The selection procedure is applied to a real measurement problem: grooves dimensioning using remote field eddy current inspection

Keywords

eddy current testing; error statistics; measurement errors; measurement theory; modelling; nonlinear estimation; parameter estimation; prediction theory; SIVIA algorithm; admissible values; data uncertainty; deterministic framework; grooves dimensioning; inclusion function; measurement vector; model selection; nonlinear bounded-error estimation; optimal model; real measurement problem; remote field eddy current inspection; set inversion procedure; worst-case criterion; Art; Current measurement; Ear; Eddy currents; Error correction; Inspection; Parameter estimation; Random variables; Stochastic processes; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 1999. IMTC/99. Proceedings of the 16th IEEE

Conference_Location

Venice

ISSN

1091-5281

Print_ISBN

0-7803-5276-9

Type

conf

DOI

10.1109/IMTC.1999.777024

Filename

777024