PřF:M8120 Spectral Analysis II - Course Information
M8120 Spectral Analysis II
Faculty of ScienceSpring 2025
- Extent and Intensity
- 2/1/0. 3 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: zk (examination).
- Teacher(s)
- doc. RNDr. Martin Kolář, Ph.D. (lecturer)
doc. Phuoc Tai Nguyen, PhD (lecturer) - Guaranteed by
- doc. RNDr. Martin Kolář, Ph.D.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science - Prerequisites
- M7120 Spectral Analysis I
Calculus of complex numbers, Vector and matrix calculus, Linear functional analysis, Basics of Fourier analysis of periodic and nonperiodic functions including convolution operators. - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Applied Mathematics for Multi-Branches Study (programme PřF, N-MA)
- Geometry (programme PřF, N-MA)
- Mathematical Modelling and Numeric Methods (programme PřF, N-MA)
- Statistics and Data Analysis (programme PřF, N-MA)
- Course objectives
- The course is aimed at providing several advanced methods of spectral analysis. The first part of the course is focused on different transforms including Z-transform, discreet Fourier transform, Laplace transform, and Radon transform and their applications in solving difference and differential equations. The second part is devoted to multiresolution analysis and wavelet which have applications in signal processing.
- Learning outcomes
- At the end of the course students should be able to: - understand and explain discrete analogs to the relevant concepts and operations from Spectral Analysis I - describe the fundamental properties and use of Z-transform, Fourier transform (discreet Fourier transform), Laplace transform and Radon transform. - Master the main techniques and use of multiresolution analysis and wavelets.
- Syllabus
- Orthogonal Polynomials: Definition and properties, Tchebychev polynomials, Legendre polynomials and applications.
- Z-transform: Definition and properties, Z-transform of element functions, the inverse Z-transform, applications to difference equations.
- Fourier transform: Quick recall of Fourier transform, uncertainty principle, discreet Fourier transform, fast Fourrier transform (FFT), approximation to the Fourier transform.
- Laplace transform: Definition and properties, Laplace transform of element functions, inverse Laplace transform, some applications.
- Radon transform: Definition and properties, relation to Fourier transform.
- Haar wavelets: introduction of scaling function and wavelet, properties, Haar decomposition and reconstruction algorithms.
- Multiresolution analysis: framework, the scaling relation, the associated wavelet and wavelet spaces, decomposition and reconstruction formulas, the scaling equation via the Fourier transform, iterative procedure for constructing the scaling function.
- Daubechies wavelets: Daubechies construction, classification, the scaling function at dyadic points. Fundamentals of wavelet analysis.
- Wavelet transform: Definition, inverse formula.
- Literature
- recommended literature
- HOWELL, Kenneth B. Principles of Fourier Analysis. Boca Raton-London-New York-Washington: Chapman & Hall, 2001, 776 pp. Studies in Advanced Mathematics. ISBN 0-8493-8275-0. info
- not specified
- BRIGHAM, E. Oran. Fast Fourier transform. Englewood Cliffs: Prentice Hall, 1974, 252 s. ISBN 0-13-307496-X. info
- VAN LOAN, Charles. Computational frameworks for the fast fourier transform. Philadelphia: Society for Industrial and Applied Mathematics, 1992, 273 s. ISBN 0-89871-285-8. info
- Teaching methods
- Lectures, exercises, homeworks
- Assessment methods
- Exams: One midterm written exam and one final written and oral exam.
- Language of instruction
- English
- Follow-Up Courses
- Further Comments
- The course is taught once in two years.
The course is taught: every week.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/sci/spring2025/M8120