Measurement and Data Processing
Code  Completion  Credits  Range  Language 

812ZMDB  Z,ZK  2  1P+1C  Czech 
 Garant předmětu:
 Lecturer:
 Tutor:
 Supervisor:
 Department of Software Engineering
 Synopsis:

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.
 Requirements:

Basic knowledge in mathematics and physics on the level of Bc courses in the 1st year at CTU in Prague and general knowledge of Fourier transform.
 Syllabus of lectures:

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, minimax 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, lockin measurements
10.Signal mining methods: Correlation estimator, Fourier transform application
11.Signal mining methods  examples
12.Review, test
 Syllabus of tutorials:

like lecture
 Study Objective:

Knowledge: The course objektive is gaining of knowledge in the field of data processing and correct interpretation of results.
Skills: The student will be able to process and correctly interpret the measured data and observations
 Study materials:

Key references:
[1] P. Hansen, V. Pereyra, G. Scherer, Least Squares Data Fitting with Applications, Baltimore, MD, USA:JHU Press, 2013, ISBN 9781421407869.
[2] J. Mandel, The Statistical Analysis of Experimental Data, Dover Publications 1984, ISBN: 9780486646664.
Recommended references:
 Note:
 Further information:
 No timetable has been prepared for this course
 The course is a part of the following study plans:

 Applications of Informatics in Natural Sciences (compulsory course in the program)