Course detail

Digital Signal Processing

CESA-SCZSAcad. year: 2023/2024

Properties of discrete and digital methods of signal processing, advantages and drawbacks. Linear signal filtering, digital filters of FIR and IIR types, design and realisation. Averaging methods of enhancement of signal in noise. Complex signals and their application, modulation and frequency trasnlation. Correlation and spectral analysis of deterministic and stochastic signals, identification of systems. Detection, inverse filtering and restoration of distorted signals in noise.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Entry knowledge

Knowledge of elements of signal and system theory, mathematics on Bc level

Rules for evaluation and completion of the course

Requirements for completion of a course are elaborated by the lecturer responsible for the course every year;
basically:
- obtaining at least 12 points (out of 24 as course-unit credit based on active presence in demonstration exercises),
- successful passing of final written exam (up to 76 points)


computer labs

Aims

To provide basic theoretical knowledge and practical experience in the area of digital signal processing, analysis and restoration
The graduate of the course
- has a good insight into the theory of digital methods of signal processing and analysis,
- is capable of assessing suitability of a particular method for a given practical task,
- has the basic application skills for implementation of these methods.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

J. JAN: Digital Signal Filtering, Analysis and Restoration. IEE Publishing, London, UK, 2000 (EN)
J.JAN: Číslicová filtrace, analýza a restaurace signálů (druhé rozsírené vydání),VUTIUM Brno, 2002 (CS)

Recommended reading

Not applicable.

Elearning

Classification of course in study plans

  • Programme SPC-STC Bachelor's 2 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Laboratory exercise

39 hod., compulsory

Teacher / Lecturer

Elearning