Scipediacontent: Scipediacontent moved page Draft Content 914725985 to Barragan et al 2017a

2021-02-02T00:58:10Z

Scipediacontent moved page Draft Content 914725985 to Barragan et al 2017a

Scipediacontent: Created page with " == Abstract == International audience; Testing analog, mixed-signal and RF circuits rep- resents the main cost component for testing complex SoCs. A promising solution to al..."

2021-02-02T00:58:03Z

Created page with " == Abstract == International audience; Testing analog, mixed-signal and RF circuits rep- resents the main cost component for testing complex SoCs. A promising solution to al..."

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== Abstract ==

International audience; Testing analog, mixed-signal and RF circuits rep- resents the main cost component for testing complex SoCs. A promising solution to alleviate this cost is the machine learning- based test strategy. These test techniques are an indirect test approach that replaces costly specification measurements by simpler signatures. Machine learning algorithms are used to map these signatures to the performance parameters. Although this approach has a number of undoubtable advantages, it also opens new issues that have to be addressed before it can be widely adopted by the industry. In this paper we present a machine learning-based test for a complex mixed-signal system –i.e. a state-of-the-art pipeline ADC– that includes digital calibration. This paper shows how the introduction of digital calibration for the ADC has a serious impact in the proposed test as calibration completely decorrelates signatures from the target specification in the presence of local mismatch.

== Original document ==

The different versions of the original document can be found in:

* [http://hal.univ-grenoble-alpes.fr/hal-01432807 http://hal.univ-grenoble-alpes.fr/hal-01432807]

* [https://hal.univ-grenoble-alpes.fr/hal-01432807 https://hal.univ-grenoble-alpes.fr/hal-01432807]

* [http://xplorestaging.ieee.org/ielx7/7919927/7926947/07926962.pdf?arnumber=7926962 http://xplorestaging.ieee.org/ielx7/7919927/7926947/07926962.pdf?arnumber=7926962],
: [http://dx.doi.org/10.23919/date.2017.7926962 http://dx.doi.org/10.23919/date.2017.7926962]

* [https://dblp.uni-trier.de/db/conf/date/date2017.html#BarraganLGPR17 https://dblp.uni-trier.de/db/conf/date/date2017.html#BarraganLGPR17],
: [https://ieeexplore.ieee.org/document/7926962 https://ieeexplore.ieee.org/document/7926962],
: [http://ieeexplore.ieee.org/document/7926962 http://ieeexplore.ieee.org/document/7926962],
: [https://academic.microsoft.com/#/detail/2599923142 https://academic.microsoft.com/#/detail/2599923142]

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Scipediacontent: Scipediacontent moved page Draft Content 914725985 to Barragan et al 2017a

Scipediacontent: Created page with " == Abstract == International audience; Testing analog, mixed-signal and RF circuits rep- resents the main cost component for testing complex SoCs. A promising solution to al..."