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Last update: Kubová Petra Ing. (22.01.2018)
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Last update: Kubová Petra Ing. (22.01.2018)
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. |
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Last update: Kubová Petra Ing. (22.01.2018)
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) |
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Last update: Kubová Petra Ing. (22.01.2018)
http://www.vscht.cz/mat/FT/CviceniFT.html http://en.wikipedia.org/wiki/Fourier_transform http://reference.wolfram.com/mathematica/ref/FourierTransform.html |
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Last update: Kubová Petra Ing. (22.01.2018)
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). |
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Last update: Pokorný Pavel RNDr. Ph.D. (13.05.2019)
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.
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Last update: Borská Lucie RNDr. Ph.D. (13.05.2019)
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. |
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Last update: Borská Lucie RNDr. Ph.D. (06.05.2019)
No requirements. |