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

Syhem Larguech 1 Florence Azaïs 1 Serge Bernard 2 Mariane Comte 1 Vincent Kerzérho 2 Michel Renovell 1
1 TEST - TEST
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
2 SmartIES - Smart Integrated Electronic Systems
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.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01233150
Contributor : Florence Azais <>
Submitted on : Tuesday, November 24, 2015 - 3:34:02 PM
Last modification on : Wednesday, August 28, 2019 - 7:12:02 PM

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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. ⟨10.1109/IMS3TW.2015.7177873⟩. ⟨lirmm-01233150⟩

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