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ε-Optimal Anomaly Detection in Parametric Tomography

Abstract : 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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Conference papers
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https://hal-utt.archives-ouvertes.fr/hal-02366204
Contributor : Jean-Baptiste Vu Van <>
Submitted on : Friday, November 15, 2019 - 5:22:17 PM
Last modification on : Saturday, November 16, 2019 - 1:42:12 AM

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Lionel Fillatre, Igor 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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