Title:

Digital Signal Processing (in English)

Code:CZSa
Ac.Year:2019/2020
Sem:Winter
Curriculums:
ProgrammeField/
Specialization
YearDuty
IT-MSC-2MGMe-Compulsory-Elective - group C
IT-MSC-2MIN-Compulsory-Elective - group C
MITAINADE-Elective
MITAINBIO-Elective
MITAINCPS-Compulsory
MITAINEMB-Elective
MITAINGRI-Elective
MITAINHPC-Elective
MITAINIDE-Elective
MITAINISD-Elective
MITAINISY-Elective
MITAINMAL-Elective
MITAINMAT-Elective
MITAINNET-Elective
MITAINSEC-Elective
MITAINSEN-Elective
MITAINSPE-Compulsory
MITAINVER-Elective
MITAINVIZ-Elective
Language of Instruction:English
Credits:5
Completion:examination (written)
Type of
instruction:
Hour/semLecturesSeminar
Exercises
Laboratory
Exercises
Computer
Exercises
Other
Hours:26130013
 ExamsTestsExercisesLaboratoriesOther
Points:511514020
Guarantor:Fučík Otto, doc. Dr. Ing. (DCSY)
Deputy guarantor:Černocký Jan, doc. Dr. Ing. (DCGM)
Lecturer:Fučík Otto, doc. Dr. Ing. (DCSY)
Rohdin Johan A., Dr. (DCGM)
Instructor:Bařina David, Ing., Ph.D. (DCGM)
Mošner Ladislav, Ing. (DCGM)
Prustoměrský Milan, Ing. (DCGM)
Vlk Jan, Ing. (DCGM)
Žmolíková Kateřina, Ing. (DCGM)
Faculty:Faculty of Information Technology BUT
Department:Department of Computer Systems FIT BUT
Schedule:
DayLessonWeekRoomStartEndLect.Gr.Groups
MonlecturelecturesA112 16:0017:501EIT 1MIT 2EIT 2MIT INTE xx
 
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.
Description:
  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.
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.
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
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
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.
 

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