After gaining fundamental knowledge about digital signal processing in the course of the same name, this course objective is to extend and deepen the knowledge of students through introduction to the more advanced algorithms and applications of digital signal processing. The goal is to get introduced to the designing methods of digital filters and adaptive systems used in the practice.

Students get introduced to the theoretical limits and designing methods of digital filters and adaptive systems in the lectures. They will learn to choose optimal structures for the realization and to design complex systems for digital signal processing.

- Ad hoc filter design - placing zeros and poles in z-plane (all-pass, notch, comb, discrete resonator). - FIR filter design based on window functions, sampling in the frequency domain, and Parks-McClellan algorithm. - IIR filter design by transforming an analog prototype filter to digital equivalent using pulse-invariant and bilinear transformation.- Adaptive systems (Wiener filter, LMS). - Multi-rate systems. - Methods of selection of structure for the digital filter realization.

The whole course of lectures (2 hours per week) is continually followed by the synchronized auditory (1 hour) and computer practice (2 hours per week). Lectures are held by the professor using the PowerPoint presentations available to the students in the .pdf format. Presentations with animations illustrate critical details from the lectures. Problems are solved in the auditory practice. The whole course is followed by the Laboratory practice for digital signal processing at the Faculty of Technical Sciences, where students gain practical experience working on the software tools for digital filter design. Practice preparation is done through the Web portal of the Department using specially designed on-line exercises. Part of the acquired theoretical knowledge is tested during the semester in the form of test, and in the final examination the entire acquired knowledge in this course is tested.