Mathematical Tools — from Fourier series to analysis of non-stationary signals
Instructor: Dr.-techn. Ing. Jan Přikryl <prikryl@fd.cvut.cz>
Lectures: Monday 09:45-11:15 K107c (group 26), Monday 13:15-14:45 K107c (group 25)
Computer sessions: Monday 11:30-13:00 K107c (group 26), Monday 15:00-16:30 K107c (group 25)
Course description
Fourier Transform, and short time Fourier Transform, have established themselves as an important tool in modern signal processing as well as in applied mathematics. The objective of this course is to establish the mathematical foundations necessary to understand general constructions useful for signal processing, update and extend the knowledge about data processing and to provide an introduction to numerical methods for solving traffic flow equations. The course includes experimental and computer projects involving individual effort.
Prerequisites: Linear Algebra, Statistial Learning, MATLAB
Texts
M. Vetterli, J. Kovacevic, and V. K. Goyal. “Fourier and Wavelet Signal Processing”. With permission of authors available from our webpage as PDF here.
S. Allen Broughton, and Kurt Bryan. ”Discrete Fourier Analysis and Wavelets”. John Wiley, 2009.
TBA
Grading
The following table lists all possible scores that can be obtained:
| Homeworks | 21 points |
| - minimum homework points | 9 points |
| Final project |
14 points |
| - minimum from the project | 7 points |
| Total | 30(+5) points |
Final grade is given by the total points obtained for homeworks and the final project. The grading scheme is as follows:
| Total points | Grade | ECTS |
|---|---|---|
| 27 to 30 | excellent | A |
| 24 to <27 | very good | B |
| 21 to <24 | good | C |
| 18 to <21 | satisfactory | D |
| 16 to <18 | sufficient | E |
| less than 16 | failed | F |