Digital Signal Processing

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.

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.

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.