Objective
This project aims to develop test strategies for mixed-signal/radio-frequency (RF) integrated devices using machine learning. The proposed efforts will be directed to two main areas, namely (a) the on-line test of mixed-signal/RF circuits when they are embedded in a System-on-Chip (SoC) or a System-in-Package (SiP) that demands high reliability and (b) the testing of RF micro-electro-mechanical systems (MEMS). The key novelty of this interdisciplinary project lies in the amalgamation of concepts from machine learning with state-of-the-art practices in very large-scale integration (VLSI) design and test, in order to address emerging and open-ended test challenges.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsradio technologyradio frequency
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
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Keywords
Call for proposal
FP7-PEOPLE-2007-4-3-IRG
See other projects for this call
Funding Scheme
MC-IRG - International Re-integration Grants (IRG)Coordinator
38031 Grenoble Cedex 1
France