Code: 12ZMD Measurement and Data Processing
Lecturer: prof. Ing. Ivan Procházka DrSc. Weekly load: 1+1 Completion: GA
Department: 14112 Credits: 2 Semester: W
Description:
Basic knowledge for the measurements and data processing and result interpretation: errors, precision, accuracy, normal distribution and its propeties, data fitting, separation of the signal from the noise.
Contents:
1.Definition of terms
2.Type of measurements and related error sources
3.Normal errors distribution
4.Normal errors distribution consequences
5.Data fitting and smoothing: interpolation, fitting, least square algorithm, mini-max methods, weighting methods, test #1
6.Data fitting and smoothing: parameters estimate, fitting strategy, solution stability
7.Data fitting and smoothing: polynomial fitting, 'best fitting' polynomial, splines, demo
8.Data editing: normal data distribution, 3*sigma, relation to data fitting, deviations from normal distribution, tight editing criteria, test #2
9.Signal mining: noise properties, correlation, lock-in measurements
10.Signal mining methods: Correlation estimator, Fourier transform application
11.Signal mining methods - examples
12.Review, test
Seminar contents:
like lecture
Recommended literature:
Key references:
[1] J. Mandel, The Statistical Analysis of Experimental Data, Dover Publications 1984, ISBN: 978-0486646664.
Recommended references:
[1] http://kfe.fjfi.cvut.cz/~blazej/en/edu/index.html

Media and tools:
none
Keywords:
Measurement, observation, precision, accuracy, fitting, signal, noise

Abbreviations used:

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