Automatic defect localization in VLSI circuits: A fusion approach based on the Dempster-Shafer theory: Automatic defect localization in VLSI circuits

Abstract : Defect localization in Very Large Integration Cir- cuits (VLSI) requires to use multi-sensor information such as electrical waveforms, emission microscopy images and frequency mapping in order to detect, localize and identify the failure. Each sensor provides a specific kind of feature modeling the evidence. Thus, the defect localization in VLSI can be summarized as a problem of data fusion with heterogeneous and imprecise information. This study illustrates how to reproduce the human decision for modeling and fusing the different multi-sensor features by using the Demspter-Shafer theory. We propose not only an automatic decision rule for mass functions computing but also confidence intervals to quantify the final decision and to bring a decision help for the analysts expertise. Finally, a case of study is reported to attest the expert decision reproducibility
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01564417
Contributeur : Le2i - Université de Bourgogne <>
Soumis le : mardi 18 juillet 2017 - 16:55:07
Dernière modification le : mercredi 12 septembre 2018 - 01:27:32

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  • HAL Id : hal-01564417, version 1

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Anthony Boscaro, Sabir Jacquir, Kevin Sanchez, Philippe Perdu, Stéphane Binczak. Automatic defect localization in VLSI circuits: A fusion approach based on the Dempster-Shafer theory: Automatic defect localization in VLSI circuits. Information Fusion, At Xi'an, China, Jul 2017, Xi'an, China. Information Fusion, At Xi'an, China, 2017, 〈https://www.researchgate.net/publication/317888594_Automatic_defect_localization_in_VLSI_circuits_A_fusion_approach_based_on_the_Dempster-Shafer_theory〉. 〈hal-01564417〉

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