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Título: | A methodology for defect detection in analog circuits based on causal feature selection |
Autor: | Leger, Gildas CSIC ORCID ; Ginés, Antonio J. CSIC ORCID; Gutiérrez, Valentín CSIC ORCID; Barragán, Manuel J. CSIC ORCID | Fecha de publicación: | 2022 | Editor: | Institute of Electrical and Electronics Engineers | Citación: | 29th IEEE International Conference on Electronics, Circuits and Systems (2022) | Resumen: | The cost of assuring test quality significantly increases when dealing with complex systems with tightly integrated AMS-RF building blocks. Machine learning-based test may be a promising solution to this issue. These tests rely on regression models trained to replace costly performance measurements by simpler test signatures. However, these regression models are targeted only at parametric performance variations in defect-free circuits. The presence of spot defects may be undetected by these tests and lead to test quality degradation and reliability issues. In this work we propose a methodology based on causal discovery algorithms to screen out these spot defects. | Descripción: | Resumen del trabajo presentado a la 29th IEEE International Conference on Electronics, Circuits and Systems (ICECS), celebrada en Glasgow (UK) del 24 al 26 de octubre de 2022. | Versión del editor: | https://doi.org/10.1109/ICECS202256217.2022.9970932 | URI: | http://hdl.handle.net/10261/337005 | DOI: | 10.1109/ICECS202256217.2022.9970932 |
Aparece en las colecciones: | (IMSE-CNM) Comunicaciones congresos |
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