MLTSRMSRFID

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

Coordinatore	INSTITUT POLYTECHNIQUE DE GRENOBLE    more  Organization address address: AVENUE FELIX VIALLET 46 city: GRENOBLE CEDEX 1 postcode: 38031 contact info Titolo: Dr. Nome: Salvador Cognome: Mir Email: send email Telefono: +33 4 76 57 48 95 Fax: +33 4 76 47 38 14
Nazionalità Coordinatore	France [FR]
Totale costo	100˙000 €
EC contributo	100˙000 €
Programma	FP7-PEOPLE Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	FP7-PEOPLE-2007-4-3-IRG
Funding Scheme	MC-IRG
Anno di inizio	2007
Periodo (anno-mese-giorno)	2007-11-01   -   2011-10-31

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	INSTITUT POLYTECHNIQUE DE GRENOBLE  Organization address address: AVENUE FELIX VIALLET 46 city: GRENOBLE CEDEX 1 postcode: 38031 contact info Titolo: Dr. Nome: Salvador Cognome: Mir Email: send email Telefono: +33 4 76 57 48 95 Fax: +33 4 76 47 38 14	FR (GRENOBLE CEDEX 1)	coordinator	0.00

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 Obiettivo del progetto (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.'