Course detail

Signals 2

FEKT-BKC-SI2Acad. year: 2023/2024

1. Random signals, processes and their characteristics

2. Spectral parameters, windowing functions

3. Discrete linear systems

4. Linear signal filtering. FIR filters

5. IIR filters, designs of digital filters

6. Signal representation and classification of real phenomena

7. Transformation and optimization of signal features

8. Linear prediction of signals

9. Machinery speech recognition

10. Identification of persons by voice

11. Time transformations, time axis warping

12. Cepstral analysis of speech signals

13. Voice analysis for security purposes

 

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Entry knowledge

Courses BPC-SI1, BPC-PP1, BPC-MA1, BPC-MA2 are required. Knowledge of the basics of systems and signal theory, mathematics at the bachelor's level and MATLAB.

 

Rules for evaluation and completion of the course

The conditions for successful completion of the course are specified in the annually updated announcement of the guarantor. The score is usually as follows:

- written test focused on counting examples max. 10 points,

- tasks in computer exercises max. 20 points,

- final exam max. 70 points.

 



All exercises are mandatory. Missed exercises must be made up by the end of the semester.


Aims

The aim of the course is to provide students with theoretical knowledge in the field of digital processing and signal analysis and practical verification of acquired skills.

The graduate of the course is familiar with deterministic and random signals, can perform signal filtering and understands voice technologies. The graduate is also able to solve practical tasks, i.e. choose and justify a suitable method and apply it.

 

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

JAN, J. Číslicová filtrace, analýza a restaurace signálů. 2. upravené a rozšířené vydání. Brno: VUTIUM, 2002. ISBN 80-214-2911-9. (CS)
TAN, L., JIANG, J. Digital Signal Processing: Fundamentals and Applications. New York: Academic Press, 2018. ISBN 978-0-12-815071-9 (EN)

Recommended reading

PSUTKA, J., MÜLLER, L., MATOUŠEK, J., RADOVÁ, V. Mluvíme s počítačem česky. Praha: Academia, 2006. ISBN 80-200-1309-0 (CS)
KOZUMPLÍK, J., JAN, J., KOLÁŘ, R. Číslicové zpracování signálů v prostředí Matlab. Brno: VUT, 2001, 72 s. ISBN 80-214-1964-4 (CS)

eLearning

Classification of course in study plans

  • Programme BKC-EKT Bachelor's, 2. year of study, summer semester, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Syllabus

1. Random signals, processes and their characteristics

2. Spectral parameters, windowing functions

3. Discrete linear systems

4. Linear signal filtering. FIR filters

5. IIR filters, designs of digital filters

6. Signal representation and classification of real phenomena

7. Transformation and optimization of signal features

8. Linear prediction of signals

9. Machinery speech recognition

10. Identification of persons by voice

11. Time transformations, time axis warping

12. Cepstral analysis of speech signals

13. Voice analysis for security purposes


Exercise in computer lab

26 hours, compulsory

Teacher / Lecturer

Syllabus

1. Analysis of random signals

2. Generation of desired random signals

3. Detection of periodic signals

4. Generation of acoustic signals

5. Determination of variable period of signals

6. Determination of short-term spectrum

7. Shot detection using entropy

8. Individual projects – first part

9. Individual projects – second part

10. Analysis of window functions (weighting)

11. Analog filter design

12. Digital filter design


eLearning