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Enhanced THz tags authentication using multivariate statistical analysis

Abstract : In this paper, we report on the unitary authentication of identically realized diffraction grating-based tags structures in the THz domain by using multivariate statistical analysis. We proceed to a dimension reduction with Principal Component Analysis (PCA) as a preprocessing step before a Gaussian classification and we evaluate the error rates. We then classify the tags using a Linear Discriminant Analysis (LDA). We demonstrate that PCA gives average error rates lower than 0.5% whereas LDA is able to classify the tags with error rates lower than 6.10-5considering its 3 first axes.
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Submitted on : Tuesday, September 10, 2019 - 11:51:11 AM
Last modification on : Friday, February 4, 2022 - 3:12:05 AM
Long-term archiving on: : Friday, February 7, 2020 - 6:31:08 PM


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  • HAL Id : hal-02282841, version 1


S. Salhi, Florent Bonnefoy, Stéphane Girard, Maxime Bernier, Nicolas Barbot, et al.. Enhanced THz tags authentication using multivariate statistical analysis. IRMMW-THz 2019 - 44th International Conference on Infrared, Millimeter, and Terahertz Waves, Sep 2019, Paris, France. pp.1-2. ⟨hal-02282841⟩



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