An Improved ADC-Error-Correction Scheme Based on a Bayesian Approach

Author

De Vito, Luca ; Michaeli, Linus ; Rapuano, Sergio

Author_Institution

Sannio Univ., Benevento

Volume

57

Issue

1

fYear

2008

Firstpage

128

Lastpage

133

Abstract

The paper presents an improved method for analog-to-digital-converter (ADC) nonlinearity correction based on a Bayesian-filtering approach. In particular, the dependence of a previous method version on the statistical characterization of the input signal has been removed. Now, the method can work on whatever stimulus signal is used without a priori knowledge about it. The proposed improvement has been validated by a numerical simulation using behavioral models provided by an ADC manufacturer and by an experiment in real ADCs.

Keywords

Bayes methods; analogue-digital conversion; error correction; numerical analysis; ADC-error-correction scheme; Bayesian-filtering approach; analog-to-digital-converter nonlinearity correction; behavioral models; probability density function; statistical characterization; Bayesian methods; Calibration; Dynamic range; Filtering; Hardware; Numerical simulation; Parameter estimation; Probability density function; Testing; Virtual manufacturing; Analog-to-digital-converter (ADC) correction; Bayes; filtering; nonlinearity; probability density function (pdf);

fLanguage

English

Journal_Title

Instrumentation and Measurement, IEEE Transactions on

Publisher

ieee

ISSN

0018-9456

Type

jour

DOI

10.1109/TIM.2007.908621

Filename

4404123