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

Programme(s)

• FP7-PEOPLE - Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)

Topic(s)

• PEOPLE-2007-4-3.IRG - Marie Curie Action: "International Reintegration Grants"

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.)