MAT-02456 Fourier Methods, 4 cr

Additional information

The course will be lectured in English every second year.

Person responsible

Antti Kuusisto

Lessons

Implementation Period Person responsible Requirements
MAT-02456 2018-01 2 Antti Kuusisto
Exam and compulsory tutorials.

Learning Outcomes

After completing the course, a student knows the definition and basic properties of Fourier series and Fourier transform. The student can represent a periodic function as a Fourier series (with real or complex coefficients) and can form new ones from known series. In addition, the student can calculate the Fourier transform of non-periodic functions for some simple example cases by using the definition and the basic properties. The student knows what is Gibbs phenomenon and can predict when it occurs in some example cases. The student knows the Dirac delta function and how to use it. A student that masters the course contents have prerequisite for understanding the practical value of the above concepts. The Fourier series of a periodic function or the Fourier transform of a non-periodic function decomposes the function into its frequency components. In practice however, the function of interest may not be available, but one only can calculate some samples of it. Then one should be able estimate the frequency decomposition by using the samples. This is done by using the discrete Fourier transform. The discovery of fast Fourier transform in 1960's was groundbreaking for signal processing and is cited as one of the most important algoritms in mathematics. The importance of the frequency decomposition stems from the ability to filter unwanted frequencies.

Content

Content Core content Complementary knowledge Specialist knowledge
1. Real Fourier series for periodic function and determining its coefficients, even and odd functions as special cases, Gibbs phenomenon.   Dirichlet conditions for fourier series convergence, expanding a function defined on a bounded interval to a periodic function.   
2. Complex Fourier series, Parseval's theroem, series as frequency decomposition.     
3. Discrete Fourier transform and its properties.  Significance of the fast Fourier transform   
4. Fourier transform of non-periodic functions: definition and basic properties, Fourier transform as frequency decomposition.   Dirac delta function, Convolution, Parseval's theorem   

Prerequisites

Course Mandatory/Advisable Description
MAT-01166 Mathematics 1 Mandatory    
MAT-01366 Mathematics 3 Mandatory    

Additional information about prerequisites
or courses of Engineering Mathematics / Mathematics in Finnish.

Correspondence of content

There is no equivalence with any other courses

Updated by: Kauhanen Janne, 12.12.2018