Maximum likelihood estimation of ADC parameters

László Balogh, István Kollár, Attila Sárhegyi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Citations (Scopus)

Abstract

Dynamic testing of analog-digital converters (ADC) is a complex task. A possible approach is using a sine wave because it can be generated with high precision. However, in the sine wave fitting method for the test of ADC's, all the available information is extracted from the measured data. Therefore, the estimated ADC parameters (ENOB, linearity errors) are not always accurate enough, and not detailed information is gained about the nonlinearity of the ADC. Generally, maximum likelihood (ML) estimation is a powerful method for the estimation of unknown parameters. However, currently it is not used for the processing of such data, because of the difficulties of formulating it, furthermore because of the numerically demanding task of the minimization of the ML cost function [9]. We have succeeded in formulating the maximum likelihood function for a sine wave excitation, and in minimizing it. The number of parameters is frightening (all comparison levels of the ADC plus parameters of the sine wave plus variance of an additive input noise), but proper handling allows to determine the best values based on the data. The proper definition of the ML function and formulation of the numerical method are presented, with results using simulation and measurement data. To our knowledge, this is the first case to solve the full maximum likelihood problem.

Original languageEnglish
Title of host publication2010 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2010 - Proceedings
Pages24-29
Number of pages6
DOIs
Publication statusPublished - Oct 18 2010
Event2010 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2010 - Austin, TX, United States
Duration: May 3 2010May 6 2010

Publication series

Name2010 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2010 - Proceedings

Other

Other2010 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2010
CountryUnited States
CityAustin, TX
Period5/3/105/6/10

ASJC Scopus subject areas

  • Instrumentation

Fingerprint Dive into the research topics of 'Maximum likelihood estimation of ADC parameters'. Together they form a unique fingerprint.

  • Cite this

    Balogh, L., Kollár, I., & Sárhegyi, A. (2010). Maximum likelihood estimation of ADC parameters. In 2010 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2010 - Proceedings (pp. 24-29). [5488286] (2010 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2010 - Proceedings). https://doi.org/10.1109/IMTC.2010.5488286