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Communication Dans Un Congrès Année : 2006

ε-Optimal Anomaly Detection in Parametric Tomography

Résumé

The paper concerns the radiographic non-destructive testing of well-manufactured objects. The detection of anomalies is addressed from the statistical point of view as a binary hypothesis testing problem with nonlinear nuisance parameters. A new detection scheme is proposed as an alternative to the classical GLR test. It is shown that this original decision rule detects anomalies with a loss of a negligible (epsiv) part of optimality with respect to an optimal invariant test designed for the "closest" hypothesis testing problem with linear nuisance parameters
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Dates et versions

hal-02366204 , version 1 (15-11-2019)

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Lionel Fillatre, Igor V. Nikiforov, Florent Retraint. ε-Optimal Anomaly Detection in Parametric Tomography. 2006 IEEE International Conference on Acoustics Speed and Signal Processing, May 2006, Toulouse, France. pp.III-277-III-280, ⟨10.1109/ICASSP.2006.1660644⟩. ⟨hal-02366204⟩
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