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Uncertainty interval evaluation using the Chi-square and Fisher distributions in the measurement process

Catelani M., Zanobini A., Ciani L.

Metrology and Measurement Systems

2010

Vol. 17, nr 2

195-204

Referring to the Guide to the Expression of Uncertainty in Measurement (GUM), the paper proposes a theoretical contribution to assess the uncertainty interval, with relative confidence level, in the case of n successive observations. The approach is based on the Chi-square and Fisher distributions and the validity is proved by a numerical example. For a more detailed study of the uncertainty evaluation, a model for the process variability has been also developed.

Introduction to the t and chi-square distribution for a more accurate evaluation of measure of the Word Error Rate in Analog-to-Digital Converters

Catelani M., Zanobini A., Ciani L.

Metrology and Measurement Systems

2008

Vol. 15, nr 4

485-490

The word error rate (WER) in an Analog to Digital Converter (ADC) is the probability of receiving an erroneous code for an input, after correction is made for gain, offset, and nonlinearity errors, and a specified allowance is made for noise. Typical causes of word errors are metastability and timing jitter of comparators within the ADC [1]. New statistical techniques which can better integrate what is sustained in the IEEE standard and in [2] have been proposed. In particular, Student and chi-square distributions have been introduced for a more accurate measurement of the word error rate in the case of n successive observations.