Digital Signal Processing

Course description

Discrete signals; Types of discrete signals; Characteristic values, correlation function. Convolution; Spectrum representation; Frequency spectrum of periodic signals, Discrete Fourier Transform (DFT); Spectral density function of non-periodic signals, Discrete Time Fourier Transform (DTFT); Practical use of DFT for multimedia signal processing; Sampling theorem; Sampling and reconstruction; Digital to analog and analog to digital conversion; Linear time-invariant systems; System and transfer functions; Transform Z; Discrete filters, Finite Impulse Response (FIR) filters, Infinite Impulse Response (IIR); Filter design, design with ideal filter approximation and Inverse Fourier Transform, design with frequency sampling, design of equiripple FIR filters; Filter banks; Practical aspects of digital signal processing for multimedia content.

Course is carried out on study programme

Multimedija 1. stopnja

Objectives and competences

The objective of the course is to familiarize students with the basic tools of digital signal processing with a multimedia approach. These are necessary for multimedia engineers and are a fundamental part of their specialized education.

With the knowledge acquired during this course, students are competent to design and implement basic systems for digital signal processing. They are competent to select the appropriate method of digital signal capturing; they understand the effects of digitizing and master basic procedures for analyzing signals in the time and frequency domains.

Finally, the acquired knowledge enables them to understand the working principles of more demanding dedicated systems for digital signal processing.

Learning and teaching methods

The lectures provide a theoretical background of the discussed chapters. We also show the solutions to simple practical digital signal processing examples. At the end of each chapter discussion, students are encourage to further reflect on the topic and search for advanced solutions for more demanding problems. We also show how to implement these solutions in practice.

Students are provided with detailed study material.

Topics discussed at the lectures are consolidated on a weekly basis during exercise hours. Students are provided with accompanying study material comprising theoretical exercise examples.

During the semester, work in the laboratory is also carried out, where students gradually learn how to use the dedicated environment and get acquinted with practical challenges. Using instructions given for each problem, students observe the effects of different digital signal processing techniques in practice.

At the end of the semester, students report their final results with a possible literature comparison.

Intended learning outcomes

Students acquire knowledge regarding the fundamental principles of design, implementation and use of digital signal processing systems.

Teaching is primarily focused towards students gaining an in-depth understanding of the basic concepts of digital signals in the time and frequency domains, on procedures and consequences of capturing, analyzing and processing signals in the discrete – digital form and their reconstruction into the analog space.

At the same time, students acquire practical experience in designing and using digital processing techniques for a variety of digital signals, including digital audio signals and images.

The study result is the ability to design and select an appropriate method for digital capturing and processing of signals, understanding the consequences of digitization and mastering the basic procedures for analyzing signals in the time and frequency space. Students learn to develop and implement basic systems for processing various digital signals.

Reference nosilca

  1. STANČIN, Sara, TOMAŽIČ, Sašo. Early improper motion detection in golf swing using wearable motion sensors: the first approach. Sensors, ISSN 1424-8220, 2013, 13(6), str. 7505-7521.
  2. STANČIN, Sara, TOMAŽIČ, Sašo. Angle estimation of simultaneous orthogonal rotations from 3D gyroscope measurements. Sensors, ISSN 1424-8220, 2011, 11(9), str. 8536-8549.
  3. STANČIN, Sara, TOMAŽIČ, Sašo. Time- and computation-efficient calibration of MEMS 3D accelerometers and gyroscopes. Sensors, ISSN 1424-8220, 2014, 14(8), str. 14885-14915.
  4. DJORDJEVIĆ, Srdjan, STANČIN, Sara, MEGLIČ, Andrej, MILUTINOVIĆ, Veljko, TOMAŽIČ, Sašo. MC Sensor – a novel method for measurement of muscle tension. Sensors, ISSN 1424-8220, 2011, 11(10), str. 9411-9425.
  5. STANČIN, Sara, TOMAŽIČ, Sašo. Motion analysis with wearable 3D kinematic sensors. ZDRAVKOVIĆ, Miloš (ur.), TRAJANOVIĆ, Miroslav (ur.), KONJOVIĆ, Zora (ur.). ICIST 2014 : proceedings, 4th International Conference on Information Society and Technology, Kopaonik, Serbia, 9-13 March 2014. Belgrade: Society for Information Systems and Computer Networks, 2014, str. 150-154.

Study materials

1. James H. MCClellan, Ronald Schafer, Mark Yoder. DSP First (2nd Edition). Pearson Education, 2015.

2. Sašo Tomažič, Leonardis Savo. Diskretni signali in sistemi. Fakulteta za elektrotehniko, 2004.

3. John G. Proakis, Dimitris K. Manolakis. Digital Signal Processing (4th Edition). Prentice Hall, 2006.

Bodi na tekočem

Univerza v Ljubljani, Fakulteta za elektrotehniko, Tržaška cesta 25, 1000 Ljubljana

E: T:  01 4768 411