SubjectsSubjects(version: 965)
Course, academic year 2019/2020
  
Fourier Transform - M413001
Title: Fourierova transformace
Guaranteed by: Department of Mathematics (413)
Faculty: Faculty of Chemical Engineering
Actual: from 2019 to 2020
Semester: winter
Points: winter s.:5
E-Credits: winter s.:5
Examination process: winter s.:
Hours per week, examination: winter s.:2/2, C+Ex [HT]
Capacity: 28 / 28 (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Level:  
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Pokorný Pavel RNDr. Ph.D.
Class: Předměty pro matematiku
Classification: Mathematics > Mathematics General
Interchangeability : AM413001, N413006
Is interchangeable with: AM413001
Examination dates   Schedule   
This subject contains the following additional online materials
Annotation -
Physical motivation, definition, properties and application of Fourier Transform, Discrete FT, Fast FT, 1-dim and higher dimensional FT, Inverse FT, convolution and deconvolution, theory of distributions (generalized functions), especially Dirac Delta Distribution and Singular Value Decomposition are presented with application in (audio and image) signal processing and in infra-red spectroscopy.
Last update: Pátková Vlasta (09.01.2018)
Literature -

R:Klíč, Volka, Dubcová: Fourierova transformace s příklady z infračervené spektroskopie. VŠCHT Praha 2002, 80-7080478-5.

A: R. Bracewell: The Fourier Transform & Its Applications, McGraw-Hill 3rd edition (1999)

Last update: Pátková Vlasta (09.01.2018)
Teaching methods -

The teaching consists of a 2-hour lecture and a 2-hour seminar a week, of individual consultation and of self-study. The final grade is based on

the exam (test + oral).

Last update: Pátková Vlasta (09.01.2018)
Syllabus -

1. Basic definitions, periodic function, convolution.

2. Dirac delta function, discretization of a continuous signal.

3. Definition of Fourier transform, its properties.

4. Fourier transform of Dirac delta function and of periodic functions.

5. Fourier transform of rectangular and triangular pulse.

6. Instrument curve.

7. Nyquist condition.

8. Discrete Fourier transform.

9. Method "zero-filling".

10. Fast Fourier transform.

11. Parseval equality.

12. Fourier series.

13. Diffusion equation.

14. Relation between Fourier transform and Fourier series.

Last update: Pokorný Pavel (13.05.2019)
Learning resources -

http://www.vscht.cz/mat/FT/CviceniFT.html

http://en.wikipedia.org/wiki/Fourier_transform

http://reference.wolfram.com/mathematica/ref/FourierTransform.html

Last update: Pátková Vlasta (09.01.2018)
Learning outcomes -

The student will be able to use Fourier Transform for signal processing and for equation solving, to find the correct sampling frequency and

the correct measurement time according to the maximal input frequency and the correct detection of close peaks, to use convolution

and deconvolution, to use Singular Value Decomposition.

Last update: Pátková Vlasta (09.01.2018)
Entry requirements -

Students are expected to have either completed the prerequisite course Mathematics A or possess the equivalent knowledge on differential and integral calculus prior to enrolling in the course.

Last update: Borská Lucie (13.05.2019)
Registration requirements -

No requirements.

Last update: Borská Lucie (06.05.2019)
Teaching methods
Activity Credits Hours
Konzultace s vyučujícími 0.9 24
Účast na přednáškách 1 28
Příprava na zkoušku a její absolvování 2.1 60
Účast na seminářích 1 28
5 / 5 140 / 140
Coursework assessment
Form Significance
Examination test 50
Oral examination 50

 
VŠCHT Praha