Course detail

Fourier Analysis

FSI-SFA-AAcad. year: 2021/2022

The course is devoted to basic properties of Fourier Analysis and illustrations of its techniques on examples. In particular, problems on reprezentations of functions, Fourier and Laplace transformations, their properties and applications are studied.

Language of instruction

English

Number of ECTS credits

4

Mode of study

Not applicable.

Guarantor

prof. Aleksandre Lomtatidze, DrSc.

Department

Institute of Mathematics (ÚM)

Learning outcomes of the course unit

Knowledge of basic topics of Fourier Analysis, manely, Fourier series, Fourier and Laplace transformations, and ability to apply this knowledge in practice.

Prerequisites

Calculus, basic konwledge of linear functional analysis, measure theory.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

The course is taught through lectures explaining the basic principles and theory of the discipline. Exercises are focused on practical topics presented in lectures.

Assesment methods and criteria linked to learning outcomes

Participation in the seminars is mandatory.
Course-unit credit is awarded on condition of having attended the seminars actively and passed the control test.
Examination has a practical and a theoretical part. In the practical part student has to illustrate the given tasks on particular examples.
Theoretical part includes questions related to the subject-matter presented at the lectures.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

The aim of the course is to familiarise students with basic topics and techniques of the Fourier analysis used in other mathematical subjects

Specification of controlled education, way of implementation and compensation for absences

Absence has to be made up by self-study using recommended literature.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

L. Grafakos, Classical Fourier Analysis: Third edition, Graduate Texts in Mathematics, 249. Springer, New York, 2014. (EN)
A. N. Kolmogorov, S. V. Fomin: Základy teorie funkcí a funkcionální analýzy, SNTL, Praha 1975. (CS)
E. W. Howel, B. Keneth: Principles of Fourier Analysis, CRC Press, 2001. (EN)
I. P. Natanson: Teorija funkcij veščestvennoj peremennoj, [Theory of functions of a real variable] ,Third edition, "Nauka'', Moscow, 1974. (RU)

Recommended reading

E. M. Stein´, G. Weiss: Introduction to Fourier Analysis on Eucledian spaces, Princeton University Press, 1971 (EN)

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme N-MAI-P Master's 1 year of study, summer semester, compulsory

  • Programme M2A-A Master's

    branch M-MAI , 2 year of study, summer semester, compulsory

  • Programme N-MAI-A Master's 1 year of study, summer semester, compulsory
    2 year of study, summer semester, compulsory
  • Programme N-AIM-A Master's 2 year of study, summer semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

prof. Aleksandre Lomtatidze, DrSc.

Syllabus

1. Space of integrable functions - definition and basic properties, dense subsets,
convergence theorems.
2. Space of quadratically integrable functions - different kinds of convergence, Fourier series.
3. Singular integral - definition, representation, application to Fourier series.
4. Trigonometric series.
5. Fourier integral.
6. Fourier transformation - Fourier transformation (FT), inverse formula, basic properties of FT, Hermit and Laguer functions, FT and convolution, applications.
7. Plancherel theorem, Hermit functions.
8. Laplace transformation.

Exercise

13 hod., compulsory

Teacher / Lecturer

prof. Aleksandre Lomtatidze, DrSc.

Syllabus

1. Space of integrable functions - definition and basic properties, dense subsets, convergence theorems.
2. Space of quadratically integrable functions - different kinds of convergence, Fourier series.
3. Singular integral - definition, representation, application to Fourier series.
4. Trigonometric series.
5. Fourier integral.
6. Fourier transformation - Fourier transformation (FT), inverse formula, basic properties of FT, Hermit and Laguer functions, FT and convolution, applications.
7. Plancherel theorem, Hermit functions.
8. Laplace transformation

Elearning

eLearning: currently opened course