Title :
An Improved ADC-Error-Correction Scheme Based on a Bayesian Approach
Author :
De Vito, Luca ; Michaeli, Linus ; Rapuano, Sergio
Author_Institution :
Sannio Univ., Benevento
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);
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2007.908621
