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

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5 Author(s)
Brahim-Belhouari, S. ; Ecole Superieure d''Electr., Gif-sur-Yvette, France ; Kieffer, M. ; Fleury, G. ; Jaulin, L.
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In this paper, the problem of model selection for measurement purpose 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

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Instrumentation and Measurement, IEEE Transactions on  (Volume:49 ,  Issue: 3 )