516-0843/01 – Signal processing (ZS)
| Gurantor department | Institute of Physics | Credits | 4 |
| Subject guarantor | doc. Dr. Ing. Michal Lesňák | Subject version guarantor | doc. Dr. Ing. Michal Lesňák |
| Study level | undergraduate or graduate | Requirement | Choice-compulsory |
| Year | 2 | Semester | summer |
| | Study language | Czech |
| Year of introduction | 2013/2014 | Year of cancellation | 2019/2020 |
| Intended for the faculties | USP, HGF | Intended for study types | Bachelor, Follow-up Master |
Subject aims expressed by acquired skills and competences
The aim of the course is to familiarize students with basic knowledge in signal processing. The theoretical findings are practically trained on simple experiments.
Teaching methods
Lectures
Summary
Compulsory literature:
DLipsman, Ronald L., and Jonathan Rosenberg. A guide to MATLAB: for beginners and experienced users. Cambridge University Press, 2006.
Mathworks Inc.: MATLAB R13 HELP, Mathworks Inc., 2002.
Recommended literature:
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Way of continuous check of knowledge in the course of semester
E-learning
Other requirements
Careful preparation for lessons.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Course Content
1. Introductory lecture. Basic concepts of experimental data processing.
2. Uncertainties kinds of uncertainties, a division of uncertainties.
3. Introduction to probability, random variables, properties and frequency distribution function.
4. Statistical analysis of one-dimensional data. Point estimates of the parameters of the position, dispersion and shape.
5. Introduction to Matlab - user interface, command window, basic commands and functions.
6. Control of the program Matlab, data entry, use toolbox, statistical toolbox.
7. Graphic data processing assistance program Matlab.
8. Presentation of data in Matlab, data from other applications and other applications.
9. Simple linear regression, regression models, nonlinear regression.
10. Using Fourier transform, properties of Fourier transform, fast Fourier transform (FFT).
11. Ideal for natural and immediate sampling, Shannon - Kotělnikův theorem.
12. Introduction to the Statigraf.
13. Individual work, implementation of simple measurements and their processing.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.