Course detail

Data Acquisition, Analysis and Processing

FEKT-MPC-ZPDAcad. year: 2022/2023

The course is dedicated to the analysis of digital signals in time and frequency domain. Emphasis is placed on the orthogonal transformation in particular DFT, fast algorithms FFT, and wavelet transformations. Part of the course is devoted to mathematical perations with time series and digital filtering.

Learning outcomes of the course unit

Student is able to:
- describe the types of physical signals,
- interpret the basic principles of data analysis methods,
- explain the importance of orthogonal transformations and give examples,
- explain the principles of FFT algorithms and methods for time - frequency analysis,
- describe the principles of wavelet transformations and discuss the results,
- explain the results of spectral and cepstral analysis,
- explain the principles of digital signal filtering,
- design a filter with the required properities.




Not applicable.

Recommended optional programme components

Not applicable.


UHLÍŘ, Jan, Pavel SOVKA a Roman ČMEJLA. Úvod do číslicového zpracování signálů. Praha: Vydavatelství ČVUT, 2003. ISBN 80-01-02799-6. (CS)
LYONS, Richard G. Understanding digital signal processing. 3rd ed. Upper Saddle River, NJ: Prentice Hall, c2011. ISBN 9780137027415. (CS)
KADLEC, František. Zpracování akustických signálů. Praha: Vydavatelství ČVUT, 2002. ISBN 80-01-02588-8. (CS)
PROAKIS, John G. Digital signal processing (4th Edition). (CS)
RABINER, Lawrence R. a Bernard GOLD. Theory and application of digital signal processing. New Jersey: Prentice-Hall, 1975. ISBN 0-13-914101-4. (EN)
SMITH, S.W. The scientist and engineer's guide to digital signal processing. California Technical Publishing, San Diego, California 1999. Dostupné z (EN)
Brandt, A.: Noise and Vibration Analysis: Signal Analysis and Experimental Procedures. Wiley, 2011 (CS)

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.
Techning methods include lectures and computer laboratorie.

Assesment methods and criteria linked to learning outcomes

up to 30 points for the evaluation computer.
up to 70 points for the final written examination.

Language of instruction


Work placements

Not applicable.

Course curriculum

1. Introduction to signal processing
2. Time series analysis
3. Convolution, Fourier transform


The aim of the course is to provide students with an overview and information in digital signal processing. The emphasis is placed to frequency and spectral analysis and digital filtering of signals.

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

The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.

Classification of course in study plans

  • Programme MPC-KAM Master's, 1. year of study, winter semester, 6 credits, compulsory

Type of course unit



26 hours, optionally

Teacher / Lecturer

Exercise in computer lab

39 hours, compulsory

Teacher / Lecturer