Code: 12ZMD Measurement and Data Processing
Lecturer: prof. Ing. Ivan Procházka DrSc. Weekly load: 1+1 Completion: GA
Department: 14112 Credits: 2 Semester: W
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.
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:

Media and tools:
Measurement, observation, precision, accuracy, fitting, signal, noise

Abbreviations used:


Mode of completion of the course:

Weekly load (hours per week):