440-4118/01 – Signal Processing in Telecommunications II (ZSK II)

Gurantor departmentDepartment of TelecommunicationsCredits4
Subject guarantorIng. Jan Skapa, Ph.D.Subject version guarantorIng. Jan Skapa, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Study languageCzech
Year of introduction2021/2022Year of cancellation
Intended for the facultiesFEIIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
SKA109 Ing. Jan Skapa, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Part-time Credit and Examination 8+8

Subject aims expressed by acquired skills and competences

The aim of the course is to teach students the basic methods and principles of 1D, 2D and multidimensional signal processing in their analysis and transmission by communication transmission chain. Attention is paid to both model (artificial) and real signal (speech signals, real images). Students will learn what tools can be used to analyze and process single and multidimensional signals. They will learn, how to compare those tools to each other in terms of their usability in specific applications. Then, students will be able to apply these tools in a specific case, critically evaluate, analyze and present the results.

Teaching methods

Experimental work in labs
Project work


The course focuses on fundamental principles and methods of signal processing during its transmission through the communication chain. Students will learn the concepts of frequency, spectrum of signal and their meanings. Furthermore, they will learn basic signal transforms and their influence on the spectrum. They will learn the meaning of Fourier series, Fourier transform, window functions and Short-time Fourier transform. They will learn the principles of 1D and 2D signals sampling and phenomena that occur during sampling (aliasing, leakage, moiré). They will learn the principles of 1D and 2D discrete Fourier transform and Discrete cosine transform. Furthermore, students will learn two-dimensional Fourier transform and its importance for optical imaging in optical communications. At the end of the course students will be introduced to the concept of kepstrum and its use in applications of speech signal processing (speech to text), speaker recognition, text to speech.

Compulsory literature:

[1] IFEACHOR, Emmanuel C., JERVIS, Barrie W.: Digital signal processing: a practical approach. 2nd ed. Harlow: Prentice Hall, 2002. ISBN 0-201-59619-9. [2] GONZALEZ, Rafael C., WOODS, Richard Eugene, EDDINS Steven L.: Digital image processing using MATLAB. 2nd ed. Spojené státy americké: Gatesmark Publishing, c2009. ISBN 978-0-9820854-0-0. [3] BLANCHET, Gérard, CHARBIT, Maurice. [i]Digital signal and image processing using MATLAB.[/i] Přeložil Antoine HERVIER. London: ISTE, 2006. ISBN 1-905209-13-4.

Recommended literature:

[1] ANTONIOU, Andreas: Digital Filtres, analysis, design and applications. 1st Edition. McGraw-Hill, 1993. ISBN-13: 978-0071454247. ISBN-10: 0071454241. [2] GONZALEZ, Rafael C., WOODS, Richard Eugene: Digital image processing. 3rd ed. Upper Saddle River: Pearson Prentice Hall, c2008. ISBN 978-0-13-168728-8. [3] MCANDREW, Alasdair. [i]Introduction to digital image processing with MATLAB.[/i] Boston: Thomson Course Technology, c2004. ISBN 0-534-40011-6.

Way of continuous check of knowledge in the course of semester

2 tests Oral exam and written test



Other requirements

No additional requirements.


Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

1. Basic types of signals. Basic signal transforms. 2. Signal spectrum, Fourier series. Fourier transform. 3. Spectra of basic types of signals. 4. Basic signal transforms and their influence on the signal spectrum. 5. 1D and 2D ideal sampling functions, sampling theorem. 6. Reconstruction of signals by ideal low-pass filter. Reconstruction with a real filter. 7. 1D and 2D discrete Fourier transform and discrete cosine transforms, their properties and comparison. 8. Short-term Fourier transform, spectrogram. 9. Window functions and their spectral properties. 10. Filtration and its influence on the signal spectrum. Telephone speech band. 11. 2D discrete Fourier transform and its relation to optical imaging systems. Airy shape. 12. Discrete wavelet transform DWT as filtering. Filter banks. 13. Multidimensional signals, their interpretation, processing and display. Principal component analysis. The teaching format is chosen so that students, through the modeling of phenomena from everyday experience, get to the mathematical relationships that describe these phenomena and then learn to use these relationships retrospectively.

Conditions for subject completion

Full-time form (validity from: 2020/2021 Summer semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 36  20
        Examination Examination 64  31 3
Mandatory attendence participation: It is allowed not to participate on 2 tutorials per semester.

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Conditions for subject completion and attendance at the exercises within ISP: Completion of all mandatory tasks within individually agreed deadlines.

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Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2022/2023 (N0714A060020) Communication and Information Technology KIT P Czech Ostrava 1 Compulsory study plan
2022/2023 (N0714A060020) Communication and Information Technology KIT K Czech Ostrava 1 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

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