A generic methodology for building efficient prediction models in the context of alternate testing

Syhem Larguech 1 Florence Azaïs 1 Serge Bernard 1 Mariane Comte 1 Vincent Kerzérho 1 Michel Renovell 1
1 SysMIC - Conception et Test de Systèmes MICroélectroniques
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : A promising solution to reduce the testing costs of analog/RF circuits is the alternate test strategy, which permits to replace costly specification measurements by simple low-cost indirect measurements. This approach has been widely explored and demonstrated in the literature on various case studies over the past twenty years. However it is clear that the efficiency of this strategy strongly depends on the quality of the regression models used to map the indirect measurements to the device specifications. In this paper, we present a generic methodology for building efficient prediction models from a large set of indirect measurements candidates. Results are illustrated on a case study for which we have experimental test data.
Type de document :
Communication dans un congrès
IMSTW: International Mixed-Signals Test Workshop, Jun 2015, Paris, France. IEEE, 2015, Mixed-Signal Testing Workshop (IMSTW), 2015 20th International. 〈10.1109/IMS3TW.2015.7177873〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01233150
Contributeur : Florence Azais <>
Soumis le : mardi 24 novembre 2015 - 15:34:02
Dernière modification le : jeudi 11 janvier 2018 - 06:27:19

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Syhem Larguech, Florence Azaïs, Serge Bernard, Mariane Comte, Vincent Kerzérho, et al.. A generic methodology for building efficient prediction models in the context of alternate testing. IMSTW: International Mixed-Signals Test Workshop, Jun 2015, Paris, France. IEEE, 2015, Mixed-Signal Testing Workshop (IMSTW), 2015 20th International. 〈10.1109/IMS3TW.2015.7177873〉. 〈lirmm-01233150〉

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