470-4118/02 – Integral and Discrete Transforms (ITDT)
| Gurantor department | Department of Applied Mathematics | Credits | 8 |
| Subject guarantor | doc. Ing. David Horák, Ph.D. | Subject version guarantor | doc. Ing. David Horák, Ph.D. |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 2 | Semester | winter |
| | Study language | English |
| Year of introduction | 2015/2016 | Year of cancellation | |
| Intended for the faculties | HGF, FEI | Intended for study types | Follow-up Master |
Subject aims expressed by acquired skills and competences
Stundent ought to manage the theory and practise of integral and discrete transforms, to get familiar with suitable approaches for the solution of concrete problems, to design an algorithm, to implement it and to make the conclusion of this solution.
Teaching methods
Lectures
Tutorials
Project work
Summary
This subject belongs to the set of basic mathematical subjects of technical university studies. Student gets know the theory and use of the Laplace transform, Z-transform, Fourier series, Fourier and Window-Fourier transform, Wavelet transform in the continuous form and discrete form as well including algorithms, efficient implementations and applications for signal processing, e.g. time-frequency analysis, compression, filtering etc.
Compulsory literature:
• Bachman G., Narici L., Becktenstein E.: Fourier and wavelet analysis, Springer, 2000.
• William L. Briggs, Van Emden Henson: THE DFT, An Owner´s Manual for the Discrete Fourier Transform, SIAM, 1995,ISBN 0-89871-342-0.
Recommended literature:
• William L. Briggs, Van Emden Henson: THE DFT, An Owner´s Manual for the Discrete Fourier Transform, SIAM, 1995,ISBN 0-89871-342-0.
Additional study materials
Way of continuous check of knowledge in the course of semester
Průběžná kontrola studia:
• Test - max. 10 bodů.
• Individuální úlohy na téma Fourierova, Laplaceova a Z-transformace - max. 20 bodů.
• Individuální projekt na implementaci a aplikaci diskrétních transformací nebo vypracování pěti implementačních úloh - max. 10 bodů.
Podmínky udělení zápočtu:
• Napsání testu - max. 10 bodů.
• Odevzdání individuálních úloh - max. 20 bodů.
• Odevzdání a obhajoba aplikačního projektu nebo pěti implementačních úloh – max. 10 bodů.
Maximální počet bodů, které lze získat ve cvičení je 40 bodů. Minimální počet bodů pro udělení zápočtu je 15 bodů.
E-learning
Other requirements
There are not defined other requirements for student.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Lectures:
• Introduction, keywords, general insight to integral and discrete transforms
• Convolution as the basic IT (convolution of functions, sequencies, vectors, n-dimensional convolution)
• Orthonormal systems and discrete orthonormal systems (Rademacher, Walsh, modified Walsh, Haar systems)
• Generalised Fourier serie and generalised discrete Fourier transform (Discrete generalised Fourier serie vs. Generalised discrete Fourier transform, harmonic analysis, Fourier serie in real and complex form, spectrum, Dirichlet's conditions, use of Fourier series for the PDE solution)
• Fourier transform (FT) (Definition of continuous and discrete FT (DFT), properties, inverse FT, matrix MF properties, two-sides DFT, two-dimensional DFT, Fast FT (FFT)
• Window FT (WFT) (Definition of window function, continuous and discrete WFT (DWFT), applications)
• Wavelet transform (WT) (Multiresolution analysis, definition of the continuous WT, properties, construction of orthonormal wavelets, discrete WT (DWT), Mallat's algorithm, fast DWT (FWT), packet decomposition, two-dimensional WT, applications)
• Laplace transform (LT) (Definition, properties, inverse LT, existence and convergence questions, use of LT for PDE solution)
• Z-transform (ZT) (Definition, inverse ZT, properties, relation to DLT, two-sides ZT, use for the solution of difference equations)
Exercises:
• Laplace transform and inverse LT
• Solution of PDE using LT
• Orthogonal and orthonormal systems of functions, Fourier serie, amplitude and phase spectrum
• Solution of PDE using Fourier series
• Fourier transform, inverse FT, convolution
• Z-transform, solution of difference equations
Computer Labs:
• Introduction of software Matlab and its toolboxes
• Discrete orthogonal systems, implementation, methods of numerical convolution
• Analysis of one-dimensional signals using DFT
• FFT algorithm and its implementation
• Discrete Window Fourier transform implementation
• Discrete Wavelet transform implementation
• Algoritms usage for analysis of signals and their filtering
Projects:
• Fourier series, Fourier transform
• Laplace transform, Z-transform
• Application project according to student's choice
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction