Predicting dynamic specifications of ADCs with a low-quality digital input signal

Xiaoqin Sheng, V.A. Kerzerho, Hans G. Kerkhoff

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    7 Citations (Scopus)
    58 Downloads (Pure)

    Abstract

    A new method is presented to test dynamic parameters of Analogue-to-Digital Converters (ADC). A noisy and nonlinear pulse is applied as the test stimulus, which is suitable for a multi-site test environment. The dynamic parameters are predicted using a machine-learning-based approach. A training step is required in order to build the mapping function using alternate signatures and the conventional test parameters, all measured on a set of converters. As a result, for industrial testing, only a simple signature-based test is performed on the Devices-Under-Test (DUTs). The signature measurements are provided to the mapping function that is used to predict the conventional dynamic parameters. The method is validated by simulation on a 12-bit 80 Ms/s pipelined ADC with a pulse wave input signal of 3 LSB noise and 7-bit nonlinear rising and falling edges. The final results show that the estimated mean error is less than 4% of the full range of the dynamic specifications.
    Original languageUndefined
    Title of host publicationProceedings of the 15th European Test Symposium, ETS 2010
    Place of PublicationWashington, DC, USA
    PublisherIEEE
    Pages158-163
    Number of pages6
    ISBN (Print)978-1-4244-5834-9
    DOIs
    Publication statusPublished - 24 May 2010
    Event15th IEEE European Test Symposium, ETS 2010 - Prague, Czech Republic
    Duration: 24 May 201028 May 2010
    Conference number: 15

    Publication series

    Name
    PublisherIEEE
    ISSN (Print)1530-1877

    Conference

    Conference15th IEEE European Test Symposium, ETS 2010
    Abbreviated titleETS
    CountryCzech Republic
    CityPrague
    Period24/05/1028/05/10

    Keywords

    • METIS-277472
    • ADC
    • IR-75544
    • EWI-19175
    • machine-learning-based
    • Test
    • pulse wave

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