Faculty of Technical Sciences

Subject: Digital Signal Processing Algorithms (17.DE111)

Native organizations units: Department of Power, Electronic and Telecommunication Engineering
General information:
 
Category Scientific-professional
Scientific or art field Telecommunications and Signal Processing
Interdisciplinary No
ECTS 10
Educational goal:

As a main course for the doctoral studies students whose major choice is digital signal processing, this course has an educational objective to provide students with all the necessary knowledge on digital signal processing and its application. It is necessary to consolidate the knowledge from graduate studies regarding digital signals in both time and frequency domains, digital filters and methods for their design. The objective of the course is to increase and deepen students` knowledge by introducing them to the advanced DSP concepts such as adaptive and multirate systems.

Educational outcome:

Main algorithms for signal processing in discrete time and the most important transformations of discrete signals, including Fast Fourier transform algorithms. Based on the acquired knowledge, students will be able to competently analyse the problem, select an appropriate digital filter class and optimal design method, design with the usage of adequate software tools and implementation on a general purpose processor or DSP platform. Students will be introduced to spectrum estimation, as well as adaptive systems, and they will gain experience with appropriate programming environments.

Course content:

•Practical aspects of A/D and D/A conversion. •Transformations of discrete signals (ZT, FTD, DFT). •Fast FT and fast convolution. •Examples of digital FIR and IIR filters. •Digital filter design (with the introduction to Matlab DSP Toolbox). •Multirate systems. •Adaptive systems. •Spectrum estimation (with the introduction to Matlab Simulink). •One part of the course is conducted through individual research and study work in the field of DSP algorithms. The study and research work is based on active study of primary scientific sources, experiments and statistic data processing, numerical simulations, and writing a paper in the narrow scientific area within the topic of the Doctoral dissertation.

Teaching methods:

The course is a combination of lectures and tutorials. Individual students' work is supported by the web portal of the Chair for Telecommunications and Signal Processing, where a number of on-line exercises is available. At the Laboratory for Digital Signal Processing at the Faculty, students obtain practical experience in the work with DSP software tools and development environments, where they implement DSP algorithms. Some of the obtained knowledge is tested during the semester in the form of simple project tasks and homework.

Literature:
Authors Title Year Publisher Language
E. Ifeachor and B. Jervis Digital Signal Processing – A Practical Approach 1993 Prentice Hall English
Milan Sečujski, Nikša Jakovlјebić, Vlado Delić Digitalna obrada signala 2019 Fakultet tehničkih nauka, Novi Sad Serbian language
Milan Sečujski, Nikša Jakovljević, Vlado Delić PowerPoint prezentacije sa predavanja i on-line vežbe preko web portala Katedre za telekomunikacije i obradu signala 2014 Interni materijal Serbian language
Mitra, S.K. Digital Signal Processing, A Computer-Based Approach 2001 McGraw-Hill, New York English
Sečujski, M. i dr. Zbirka zadataka iz digitalne obrade signala 2014 Fakultet tehničkih nauka, Novi Sad Serbian language
Proakis, J.G., Manolakis, D.G. Digital Signal Processing : Principles, Algorithms, Applications 1996 Prentice Hall, New Jersey English
Knowledge evaluation:
Course activity Pre-examination Obligations Number of points
Project Yes Yes 30.00
Written part of the exam - tasks and theory No Yes 50.00
Homework Yes Yes 5.00
Homework Yes Yes 5.00
Homework Yes Yes 5.00
Homework Yes Yes 5.00
Lecturers:
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vanr. prof. dr Jakovljević Nikša

Associate Professor

Lectures
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prof. dr Sečujski Milan

Full Professor

Lectures

Faculty of Technical Sciences

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Contact:

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Phone:  (+381) 21 450 810
(+381) 21 6350 413

Fax : (+381) 21 458 133
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© 2024. Faculty of Technical Sciences.