Course detail

Digital Signal Processing (in English)

FIT-CZSaAcad. year: 2023/2024

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

Entry knowledge

Not applicable.

Rules for evaluation and completion of the course

  • 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.

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.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

(EN)

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme IT-MSC-2 Master's

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

  • Programme IT-MSC-2 Master's

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

  • Programme MIT-EN Master's 0 year of study, winter semester, elective

  • Programme MITAI Master's

    specialization NSPE , 0 year of study, winter semester, compulsory
    specialization NBIO , 0 year of study, winter semester, elective
    specialization NSEN , 0 year of study, winter semester, elective
    specialization NVIZ , 0 year of study, winter semester, elective
    specialization NGRI , 0 year of study, winter semester, elective
    specialization NADE , 0 year of study, winter semester, elective
    specialization NISD , 0 year of study, winter semester, elective
    specialization NMAT , 0 year of study, winter semester, elective
    specialization NSEC , 0 year of study, winter semester, elective
    specialization NISY up to 2020/21 , 0 year of study, winter semester, elective
    specialization NCPS , 0 year of study, winter semester, compulsory
    specialization NHPC , 0 year of study, winter semester, elective
    specialization NNET , 0 year of study, winter semester, elective
    specialization NMAL , 0 year of study, winter semester, elective
    specialization NVER , 0 year of study, winter semester, elective
    specialization NIDE , 0 year of study, winter semester, elective
    specialization NEMB , 0 year of study, winter semester, elective
    specialization NISY , 0 year of study, winter semester, elective
    specialization NEMB up to 2021/22 , 0 year of study, winter semester, elective

  • Programme IT-MGR-1H Master's

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

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. Dr. Ing. Otto Fučík
prof. Ing. Hynek Heřmanský, Dr. Eng.
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

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

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

doc. Dr. Ing. Otto Fučík

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.

Elearning

eLearning: currently opened course