1. komponenta

Lecture type	Total
Lectures	30
Exercises	30

* Load is given in academic hour (1 academic hour = 45 minutes)

COURSE AIMS AND OBJECTIVES: The aim of the course is to introduce students to several important and interesting topics related to signal processing, with an emphasis on applications in sound and visual signal processing

COURSE DESCRIPTION AND SYLLABUS:
1. Connection of sound and Fourier series. Basic properties of Fourier series.
2. Discrete Fourier analysis and discrete Fourier transformation.
3. Sampling theorem.
4. Fast Fourier transformation.
5. Discrete cosine transformation.
6. Discrete time filters.
7. Low-pass and high-pass filters.
8. Wavelets, motivation and basic examples.
9. Discrete wavelet transformation
10. Digital image, basic operations on digital images.
11. Image operations based on filters.
12. Tensor products and application to operations on digital images.

1. Linear Algebra, Signal Processing, and Wavelets - A Unified Approach, O. Ryan, Springer, 2019.
2. Discrete Fourier Analysis and Wavelets, 2. izdanje, S. A. Broughton, K. Bryan, Wiley, 2018.
3. Applied Fourier Analysis, T. Olson, Birkhäuser, 2017.

Enrollment :
Passed : Linear algebra 2
Passed : Numerical mathematics

Izborni predmet 1, 2 - Regular study - Mathematics

Izborni predmet 1, 2 - Regular study - Mathematics