Course detail

Digital Signal Processing (in English)

FIT-CZSaAcad. year: 2020/2021

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.

Language of instruction

English

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

doc. Dr. Ing. Otto Fučík

Department

Department of Computer Systems (UPSY)

Offered to foreign students

Of all faculties

Learning outcomes of the course unit

Not applicable.

Prerequisites

Not applicable.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

  • 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.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

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.

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

Not applicable.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

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

Classification of course in study plans

  • Programme IT-MSC-2 Master's

    branch MIN , 0 year of study, winter semester, compulsory-optional

  • Programme MITAI Master's

    specialization NISY , 0 year of study, winter semester, elective
    specialization NADE , 0 year of study, winter semester, elective
    specialization NBIO , 0 year of study, winter semester, elective
    specialization NCPS , 0 year of study, winter semester, compulsory
    specialization NEMB , 0 year of study, winter semester, elective
    specialization NHPC , 0 year of study, winter semester, elective
    specialization NGRI , 0 year of study, winter semester, elective
    specialization NIDE , 0 year of study, winter semester, elective
    specialization NISD , 0 year of study, winter semester, elective
    specialization NMAL , 0 year of study, winter semester, elective
    specialization NMAT , 0 year of study, winter semester, elective
    specialization NNET , 0 year of study, winter semester, elective
    specialization NSEC , 0 year of study, winter semester, elective
    specialization NSEN , 0 year of study, winter semester, elective
    specialization NSPE , 0 year of study, winter semester, compulsory
    specialization NVER , 0 year of study, winter semester, elective
    specialization NVIZ , 0 year of study, winter semester, elective

  • Programme IT-MGR-1H Master's

    branch MGH , 0 year of study, winter semester, recommended course

  • Programme IT-MSC-2 Master's

    branch MGMe , 0 year of study, winter semester, compulsory-optional

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. Dr. Ing. Otto Fučík
M.Sc. Johan Andréas Rohdin, Ph.D.

Syllabus

  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

Fundamentals seminar

13 hod., compulsory

Teacher / Lecturer

Ing. David Bařina, Ph.D.
Ing. Jan Vlk, Ph.D.
Ing. Kateřina Žmolíková, Ph.D.
Ing. Milan Prustoměrský
Ing. Ladislav Mošner

Syllabus

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.

Project

13 hod., compulsory

Teacher / Lecturer

Ing. Kateřina Žmolíková, Ph.D.
Ing. Ladislav Mošner
Ing. Jan Vlk, Ph.D.
Ing. Milan Prustoměrský
Ing. David Bařina, Ph.D.

Syllabus

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.