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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2024/2025
Faculties | School elective courses | ECTS courses catalogue | Settings | Česká verze
Welcome page > Faculty of Information Technology > Department of Applied Mathematics > Statistical Modelling Lab
NOTICE: Study plans for the following academic year are available.

Statistical Modelling Lab

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Code Completion Credits Range Language
NI-LSM KZ 5 3C Czech
Course guarantor:
Kamil Dedecius
Lecturer:
Kamil Dedecius
Tutor:
Kamil Dedecius
Supervisor:
Department of Applied Mathematics
Synopsis:

The subject is oriented on a single and multi-target tracking. The student both learns the existing methods and tries to implement them. The stress is put on the effective use of the available information and its modeling using numpy and scipy. The second half of the semester is focused on the design of methods and algorithms, and analyses of their properties. At this point, the subject is on the border of own research and may result in the topic of final work (diploma or bachelor thesis).

Requirements:

BI-LIN, BI-ZMA

Ideally BI-PST too.

Syllabus of lectures:

1. Introduction into statistical modelling, Bayesian approach.

2. Linear model, prior and posterior information.

3. Kalman filter, single target tracking.

4. Kalman filtering in clutter.

5. PDA filter.

6. PDA filtering continued.

7. Project: Assignment.

8. Project: Analysis of the state of the art.

9. Project: Design of suitable solutions.

10. Project: Implementation of proposed solutions.

11. Project: Analysis of results.

12. Project: Assessment

Syllabus of tutorials:

1. Introduction into statistical modelling, Bayesian approach.

2. Linear model, prior and posterior information.

3. Kalman filter, single target tracking.

4. Kalman filtering in clutter.

5. PDA filter.

6. PDA filtering continued.

7. Project: Assignment.

8. Project: Analysis of the state of the art.

9. Project: Design of suitable solutions.

10. Project: Implementation of proposed solutions.

11. Project: Analysis of results.

12. Project: Assessment

Study Objective:
Study materials:

1. E. Brekke: Fundamentals of sensor fusion. NTNU, 2021

2. X. Rong Li and Y. Bar-Shalom, Tracking in clutter with nearest neighbor filters: analysis and performance, IEEE Transactions on Aerospace and Electronic Systems, vol. 32, no. 3, pp. 9951010, Jul. 1996, doi: 10.1109/7.532259.

3. Y. Bar-shalom, F. Daum, and J. I. M. Huang, The probabilistic data association filter, IEEE Control Systems, vol. 29, no. 6, pp. 82100, Dec. 2009, doi: 10.1109/MCS.2009.934469.

Note:

Since 2023, the subject is oriented on single- and multi-target tracking. More information about the subject (in Czech) can be found on https://courses.fit.cvut.cz/NI-LSM.

Further information:
https://courses.fit.cvut.cz/NI-LSM/
Time-table for winter semester 2024/2025:
Time-table is not available yet
Time-table for summer semester 2024/2025:
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
Tue
roomTH:A-1442
Dedecius K.
18:00–20:30
(parallel nr.101)
Thákurova 7 (budova FSv)
Wed
Thu
Fri
The course is a part of the following study plans:
Data valid to 2025-05-19
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