Faculty of Information Technology, BUT

Course details

Digital Signal Processing (in English)

CZSa Acad. year 2019/2020 Winter semester 5 credits

Introduction to digital signal processing, sampling and quantization, Frequency analysis of digital signals, Principles of digital filters, Digital filter design, Practical implementation of digital filters. Processing in frequency domain, Sub-band signal processing, changing the sampling frequency, Wavelet analysis and synthesis, Random signals, State space representation, System identification, Wiener and Kalman filtering, Vector signal processing.

Guarantor

Deputy Guarantor

Language of instruction

English

Completion

Examination (written)

Time span

26 hrs lectures, 13 hrs exercises, 13 hrs projects

Assessment points

51 exam, 15 half-term test, 14 exercises, 20 projects

Department

Lecturer

Fučík Otto, doc. Dr. Ing. (DCSY FIT BUT)
Rohdin Johan A., Dr. (DCGM FIT BUT)

Instructor

Bařina David, Ing., Ph.D. (DCGM FIT BUT)
Mošner Ladislav, Ing. (DCGM FIT BUT)
Prustoměrský Milan, Ing. (DCGM FIT BUT)
Vlk Jan, Ing. (DCGM FIT BUT)
Žmolíková Kateřina, Ing. (DCGM FIT BUT)

Learning objectives

To refresh basic knowledge of signals and systems and to make students familiar with more advanced topics linked to artificial intelligence, cyber-physical systems, speech and sound processing and other related domains. To provide students with sufficient mathematical background allowing to understand conference and journal papers dealing with signal processing topics, and allowing for own independent work in signal processing. To provide students with sufficient practical knowledge for implementing and integrating signal processing algorithms.

Study literature

  • Oppenheim A.V., Wilski A.S.: Signals and systems, Prentice Hall, 1997.  
  • Jan J., Číslicová filtrace, analýza a restaurace signálů, VUT v Brně, VUTIUM, 2002, ISBN 80-214-1558-4. 
  • Mallat S, A Wavelet Tour of Signal Processing (Third Edition), Academic Press, 2009, ISBN 9780123743701

Fundamental literature

  • Oppenheim A.V., Wilski A.S.: Signals and systems, Prentice Hall, 1997.  
  • Jan J., Číslicová filtrace, analýza a restaurace signálů, VUT v Brně, VUTIUM, 2002, ISBN 80-214-1558-4. 
  • Mallat S, A Wavelet Tour of Signal Processing (Third Edition), Academic Press, 2009, ISBN 9780123743701

Syllabus of lectures

  1. Introduction to digital signal processing, sampling and quantization.
  2. Frequency analysis of digital signals, DTFT, DFT and FFT. 
  3. Principles of digital filters. 
  4. Digital filter design. 
  5. Practical implementation of digital filters.
  6. Processing in frequency domain
  7. Sub-band signal processing, changing the sampling frequency.
  8. Wavelet analysis and synthesis.
  9. Random signals - correlation and power spectral density.
  10. State space representation. 
  11. System identification.
  12. Wiener and Kalman filtering.
  13. Vector signal processing

Syllabus of numerical exercises

Demonstration exercises (1h per week) immediately follow the lectures and demonstrate the taught techniques to the students based on real code, mostly in python and Matlab/Octave. All codes will be available to the students. Two homeworks (to be solved during the semester) are based on these exercises.

Syllabus - others, projects and individual work of students

The project is assigned in combination with another master course based on students specialization (for example in speech processing, or cyber-physical systems). It is solved in teams of up to 5 students, a report and short presentation are required. The data for projects will be provided, or acquired by the students. Examples of projects: 
  1. Simple signal processing for a microphone array  
  2. Estimation of transfer function of a mechanical system 
  3. Changing the properties of sound using time-frequency processing. 
  4. Sub-band audio coding.

Progress assessment

  • Solving and submitting solution of two home-works during the semester (7pts each, total 14pts) 
  • Half-semestral exam (15pts) 
  • Submission and presentation of project (20pts)
  • Semestral exam, 51pts, requirement of min. 17pts.

Schedule

DayTypeWeeksRoomStartEndLect.grpGroupsInfo
Monlecturelectures A112 16:0017:50 1EIT 1MIT 2EIT 2MIT INTE xx
Moncomp.lab3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13. of lectures N203 18:0018:50 1EIT 1MIT 2EIT 2MIT INTE

Course inclusion in study plans

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