CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2024/2025

# Selected Mathematical Methods

The course is not on the list Without time-table
Code Completion Credits Range Language
BI-VMM Z,ZK 4 2P+2C Czech
Garant předmětu:
Lecturer:
Tutor:
Supervisor:
Department of Applied Mathematics
Synopsis:

We start reviewing geometric properties of linear spaces with inner product. Next, we introduce and analyze the discrete Fourier transform (DFT) and its fast implementation (FFT).

Further we deal with differential calculus of functions involving multiple variables. We present methods for the localization of extreme values of functions. For this purposes, we study normed linear spaces and quadratic forms. In addition, we introduce the least square method.

The last part of the course is devoted to optimization and duality. The linear programming and the Simplex method is analyzed in more detail.

Requirements:

The fundamental knowledge of mathematical analysis and linear algerbra is required as they are given in BI-ZMA and BI-LIN.

Syllabus of lectures:

1. Complex numbers, complex function of complex variable, exponential function.

2. Fourier series.

3. Hilbert spaces of finite dimension, unitary matrices.

4. Discrete Fourier transformation (DFT) and Fast Fourier transform (FFT).

5. Basic objects from theory of multivariate functions.

6. (Constrained) extrema of multivariate functions.

7. General optimization problem.

8. Weak and strong duality.

9. Linear programming (introduction, formulation).

10. Linear programming (problem in standard form).

11. SIMPLEX algorithm.

12. Examples and applications of Linear programming.

Syllabus of tutorials:

1. Complex numbers, complex function of complex variable, exponential function.

2. Fourier series.

3. Hilbert spaces of finite dimension, unitary matrices.

4. Discrete Fourier transformation (DFT) and Fast Fourier transform (FFT).

5. Basic objects from theory of multivariate functions.

6. (Constrained) extrema of multivariate functions.

7. General optimization problem.

8. Weak and strong duality.

9. Linear programming (introduction, formulation).

10. Linear programming (problem in standard form).

11. SIMPLEX algorithm.

12. Examples and applications of Linear programming.

Study Objective:

The goal of the course is to improve student's mathematical skills and to present classical mathematical methods with applications in IT.

Study materials:

Howard Karloff: Linear Programming.

O. Julius Smith: Mathematics of the Discrete Fourier Transform with Audio Applications.

J.Kopáček: Matematika nejen pro fyziky II (lecture notes in czech).

Note:
Further information:
https://courses.fit.cvut.cz/BI-VMM/
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2024-06-16
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