Course detail

Introduction to Signal Processing

FSI-RSZAcad. year: 2020/2021

The subject gives the introduction to theory of digital signal processing of one dimensional signals. The gained knowledge will be used in practical examples using Matlab software. The emphasis in the subject is on understanding the basic terms and processing method of the field (signal, sampling, discretization, quantizing, convolution, Fourier transform, IIR and FIR filters)

Learning outcomes of the course unit

The students will be able after passing the course to understand the basic terms in the signal processing field, analyze onedimensional signal and design filter for given application using Matlab.


fundamentals of Matlab (or Octave), in particular: working with matrices, vectors, simple graphs, basics of programming


Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Zaplatílek K., Doňar B.: Matlab - začínáme se signály, BEN,Praha, 2006
Jan. J.: Číslicová filtrace, analýza a restaurace signálů, VUT v Brně, 1997
SMITH, S. W. The Scientist and Engineer’s Guide to Digital Signal Processing. California Technical Pub., 1997. 626 p. ISBN: 9780966017632.

Planned learning activities and teaching methods

The course is taught through lectures explaining the basic principles and theory of the discipline. Exercises are focused on practical topics presented in lectures.

Assesment methods and criteria linked to learning outcomes

Course unit credist will be awarded based on evaluation of the project. In the project the student has to prove the ability to solve given task: design of the filter for onedimensional signal using Matlab

Language of instruction


Work placements

Not applicable.


The goal of the subject is to introduce to the students the fundamentals of signal processing, mainly the diginal processing of one dimensional signals. The practical tasks realized in Matlab are the essential part of the course.

Specification of controlled education, way of implementation and compensation for absences

Attendance at practical training is obligatory. Attendance is checked systematically by the teachers, as well as students’ active participation in the seminars and fundamental knowledge. Unexcused absence is the cause for not awarding the course-unit credit. One absence can be compensated for by attending a seminar with another study group in the same week, or by solving supplemental tasks. Longer absence may be compensated for by solving supplemental tasks according to teacher’s requirements.

Classification of course in study plans

  • Programme N-IMB-P Master's

    specialization BIO , 1. year of study, winter semester, 5 credits, compulsory-optional
    specialization IME , 1. year of study, winter semester, 5 credits, compulsory

  • Programme N-MET-P Master's, 1. year of study, winter semester, 5 credits, compulsory

Type of course unit



13 hours, optionally

Teacher / Lecturer


1. Signal: definition, classification, why we need to process, applications.
2. Continuous / discrete signal, sampling, discretization, quantizing
3. Continuous systems and its description
4. Discrete systems
5. Linear systems, superposition principle, decomposition
6. Convolution
7. Fourier transform
8. Fourier transform, properties
9. Digital filters, introduction
10. IIR filters
11. FIR filters
12. Applications
13. Kalman filtering

Computer-assisted exercise

26 hours, compulsory

Teacher / Lecturer


1. Matlab review. Signal Processing Toolbox.
2. Reading the signal, signal generation
3. Original (time) domain analysis
4. SPTool
5. Convolution
6. Correlation analysis
7. Spectral analysis - introduction
8. Discrete Fourier transform
9. Filtering - introduction
10. Filtering – using FDATool
11. Filtering, applications
12. Frequency analysis in time, spectrogram
13. Kalman filter, nonlinear versions of KF