Seminar of Applied Mathematics

Course guarantor:

Milan Krbálek

Lecturer:

Tutor:

Milan Krbálek

Supervisor:

Department of Mathematics

Synopsis:

1. Defectoscopy and acoustic emission.

2. Machine learning.

3. Traffic flow dynamics. Dynamics of crowd movement.

4. Digital image processing.

5. Dynamic pricing.

6. Statistical predictions in economics, sociology and psychology.

7. Application of random matrix theory.

Requirements:

Syllabus of lectures:

Syllabus of tutorials:

Study Objective:

Study materials:

Key references:

[1] Chollet, F., Dee: Learning with Python, 2018.

[2] Mehta, M. L.: Random Matrices (3rd ed.), Academic Press, New York, 2004.

[3] Gonzales R. C., Woods R. E.: Digital Image Processing (4th ed.), Pearson, 2018.

Recommended references:

[4] Treiber, M., Kesting, A.: Traffic Flow Dynamics, Springer 2013.

[5] Schadschneider, A., Chowdhury, D., Nishinari, K.: Stochastic Transport in Complex Systems, Elsevier Science & Technology, 2010.

Note:

Time-table for winter semester 2024/2025:

Time-table is not available yet

Time-table for summer semester 2024/2025:

Time-table is not available yet

The course is a part of the following study plans:

• Aplikovaná algebra a analýza (elective course)
• Aplikované matematicko-stochastické metody (compulsory course in the program)
• Matematické inženýrství - Matematická informatika (elective course)
• Matematické inženýrství - Matematické modelování (elective course)