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Machine Learning-Based Test Solutions for Reliable Mixed-Signal/RF Integrated Devices

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.

Field of science

  • /natural sciences/computer and information sciences/artificial intelligence/machine learning

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

INSTITUT POLYTECHNIQUE DE GRENOBLE
Address
Avenue Felix Viallet 46
38031 Grenoble Cedex 1
France
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 100 000
Administrative Contact
Salvador Mir (Dr.)