Course detail

Signals and Systems

FIT-ISSAcad. year: 2017/2018

Continuous and discrete time signals and systems. Spectral analysis in continuous time - Fourier series and Fourier transform. Systems with continuous time. Sampling and reconstruction. Discrete-time signals and their frequency analysis: Discrete Fourier series and Discrete-time Fourier transform. Discrete systems. Two-dimensional signals and systems. Random signals.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

prof. Dr. Ing. Jan Černocký

Department

Department of Computer Graphics and Multimedia (UPGM)

Learning outcomes of the course unit

Students will learn and understand basis of  description and analysis of discrete and continuous-time signals and systems. They will also obtain practical skills in analysis and filtering in MATLAB.

Students will deepen their knowledge in mathematics and statistics and apply it on real problems of signal processing. During the course, they will get acquainted with math- and visualization-SW Matlab.

Prerequisites

basic maths and statistics

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Study evaluation is based on marks obtained for specified items. Minimimum number of marks to pass is 50.

Course curriculum

    Syllabus of lectures:
    1. Digital filters - fundamentals and practical usage
    2. Frequency analysis using DFT - fundamentals and practical usage
    3. Image processing (2D signals) - fundamentals and practical usage
    4. Random signals - fundamentals and practical usage
    5. Applications of signal processing and introduction to theory
    6. Frequency analysis of continuous time signals
    7. Continuous time systems
    8. From continuous to discrete - sampling, quantization
    9. Discrete signal sin more detail
    10. Digital filtering in more detail
    11. Random signals in more detail
    12. Applications and advanced topics of signal processing

    Syllabus of computer exercises:
    1. Introduction to MATLAB
    2. Projection onto basis, Fourier series
    3. Processing of sounds
    4. Image processing
    5. Random signals
    6. Sampling, quantization and aliasing

    Syllabus - others, projects and individual work of students:
    The individual project aims at image processing, see  http://www.fit.vutbr.cz/study/courses/ISS/public/#proj

Work placements

Not applicable.

Aims

To learn and understand basic theory of signals and linear systems with continuous and discrete time. To introduce  to random signals. The emphasis of the course is on spectral analysis and linear filtering - 2 basic building blocks of modern communication systems.

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

  • participation in computer labs is not checked but active participation and presentation of results to the tutor is evaluated by 2 pts.
  • Groups in computer labs are organized according to inscription into schedule frames.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Basic literature

Oppenheim A.V., Wilski A.S.: Signals and systems, Prentice Hall, 1997

Recommended reading

http://www.fit.vutbr.cz/study/courses/ISS/public/ Jan, J., Kozumplík, J.: Systémy, procesy a signály. Skriptum VUT v Brně, VUTIUM, 2000. Šebesta V.: Systémy, procesy a signály I., Skriptum VUT v Brně, VUTIUM, 1997. Jan J., Číslicová filtrace, analýza a restaurace signálů, VUT v Brně, VUTIUM, 2002, ISBN 80-214-1558-4.

Classification of course in study plans

  • Programme IT-BC-3 Bachelor's

    branch BIT , 2 year of study, winter semester, compulsory

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

prof. Dr. Ing. Jan Černocký

Syllabus

  1. Digital filters - fundamentals and practical usage
  2. Frequency analysis using DFT - fundamentals and practical usage
  3. Image processing (2D signals) - fundamentals and practical usage
  4. Random signals - fundamentals and practical usage
  5. Applications of signal processing and introduction to theory
  6. Frequency analysis of continuous time signals
  7. Continuous time systems
  8. From continuous to discrete - sampling, quantization
  9. Discrete signal sin more detail
  10. Digital filtering in more detail
  11. Random signals in more detail
  12. Applications and advanced topics of signal processing

Exercise in computer lab

12 hod., optionally

Teacher / Lecturer

prof. Dr. Ing. Jan Černocký

Syllabus

  1. Introduction to MATLAB
  2. Projection onto basis, Fourier series
  3. Processing of sounds
  4. Image processing
  5. Random signals
  6. Sampling, quantization and aliasing

Project

14 hod., optionally

Teacher / Lecturer

prof. Dr. Ing. Jan Černocký