Article

# Influence of frequency errors in the variance of the cumulative histogram [in ADC testing]

Dept. of Electr. & Comput. Eng., Tech. Univ. Lisbon

IEEE Transactions on Instrumentation and Measurement (Impact Factor: 1.36). 05/2001; DOI: 10.1109/19.918166 Source: IEEE Xplore

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**ABSTRACT:**This paper reports estimation of gain error, offset error and Effective Number of Bits (ENOB) of an Analog to Digital Converter (ADC) using histogram technique for sine wave as input test signal. Computation of code transition levels of ADC transfer characteristics is done by collecting large number of samples of full scale sine wave and estimating cumulative histogram. Gain error and offset error are determined from first and last code transition levels of ADC transfer characteristics. ENOB is determined from actual rms error and ideal rms error. Simulation of 5–8bit ADC transfer characteristics is done and ADC parameters are estimated by introducing arbitrary nonlinearity errors. Comparison of simulation results of this method with existing methods is done and improvement in results is obtained as compared to existing. The main aim of dynamic testing is to determine functional parameters of an ADC which are responsible for the accuracy, resolution, speed and linearity of the conversion process.Measurement. 01/2009; 42(4):570-576. -
##### Article: Precision of Independently Based Gain and Offset Error of an ADC Using the Histogram Method

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**ABSTRACT:**Two of the parameters that are determined when testing an analog-to-digital converter (ADC) are the gain and offset errors. One of the ways to define these two parameters is called ldquoindependently based.rdquo In this paper, we derive the precision of the gain and offset errors estimated with the histogram test method affected by additive noise.IEEE Transactions on Instrumentation and Measurement 04/2009; · 1.36 Impact Factor - [Show abstract] [Hide abstract]

**ABSTRACT:**The presence of additive noise in an analogue to digital converter test setup or in the converter itself causes a bias in the estimation of its gain and offset error when using the Histogram Test Method. This will be demonstrated here by analytically determining the estimation error as a function of the sinusoidal stimulus signal amplitude and the noise standard deviation. A closed form approximate expression will be proposed for the computation of the bias. The results presented are numerically validated using a Monte Carlo procedure.01/2009;

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