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Updated: Jun 28, 2026

A Tactile Automated Passive-Finger Stimulator (TAPS)
Published on: June 3, 2009
Calibration and measurement control based on Bayes statistics
K M Hangos1, L Leisztner, M Kárný
1Computer and Automation Institute Hungarian Academy of Sciences PO Box 63 Budapest H1502 Hungary.
Abstract:
The Bayesian methodology described in this paper has the inherent capability of choosing, from calibration-type curves, candidates which are plausible with respect to measured data, expert knowledge and theoretical models (including the nature of the measurement errors). The basic steps of Bayesian calibration are reviewed and possible applications of the results are described in this paper. A calibration related to head-space gas chromatographic data is used as an example of the proposed method. The linear calibration case has been treated with a log-normal distributed measurement error. Such a treatment of noise stresses the importance of modelling the random constituents of any problem.
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