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Zpracování experimentálních dat

Type of study Bachelor
Language of instruction Czech
Code 653-2239/01
Abbreviation ZED
Course title Zpracování experimentálních dat
Credits 5
Coordinating department Department of Materials Engineering and Recycling
Course coordinator Ing. Lukáš Halagačka, Ph.D.

Subject syllabus

1. Introduction, basic concept of Matlab, license files, installation, first script,
2. Reading and writing to a file, operations on matrices and vectors, algebraic operations on matrices and their elements, basic linear algebra problems: determinant, inverse and transpose matrices, solving systems of linear equations
3. Fundamentals of code structuring, inner and outer functions, creation of structures
4. Comparison of values, conditions, cycles,
5. Interpolation, numerical integration and derivation
6. Visualization of experimental data, graphs
7. Fourier transform, convolution, FFT, frequency analysis
8. Practical problem: conversion of a complex THz signal from time domain to frequency domain
9. Creation of parametric model, comparison of model and experimental data
10. Parametric model optimization, simplex, gradient methods
11. Practical task: fitting the parameters of a damped harmonic oscilátor
11. Convergence criteria of fitting procedure, error and correlation analysis
12. Practical problem: signal analysis of RLC oscillator and determination of circuit parameters
13. Code optimization, profiling tools

Literature

ZAPLAŤÍLEK, Karel, Matlab pro začátečníky, BEN - technická literatura, 2014, ISBN: 80-7300-175-6
VALENTINE, Daniel T.; HAHN, Brian H. Essential MATLAB for engineers and scientists. Academic Press, 2022.
ATTAWAY, Dorothy C. Matlab: a practical introduction to programming and problem solving. Butterworth-Heinemann, 2013
HUGHES, Ifan; HASE, Thomas. Measurements and their uncertainties: a practical guide to modern error analysis. OUP Oxford, 2010.

Advised literature

ATTAWAY, Dorothy C. Matlab: a practical introduction to programming and problem solving. Butterworth-Heinemann, 2022.
HILL, Christian. Learning scientific programming with Python. Cambridge University Press, 2020.