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)
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    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
    Number of pages6
    ISBN (Print)978-1-4244-5834-9
    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

    ISSN (Print)1530-1877


    Conference15th IEEE European Test Symposium, ETS 2010
    Abbreviated titleETS
    CountryCzech Republic


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

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