Course objectives:
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The aim of the course is to introduce students to estimation theory deals with estimation of unknown variables, random variables and random processes based on apriori information and measurements.
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Requirements on student
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Three tests, elaboration of three written reports and to understand content of the lectures.
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Content
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1. Introduction to estimation theory
2. Random variables, stochastic processes and their description
3. Mean square error optimal estimate
4. Maximum likelihood optimal estimate
5. Linear stochastic system
6. Kalman filter
7. State estimation of continuous system with discrete-time measurements
8. Optimal smoothing
9. Kalman - Bucy filter
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Activities
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Fields of study
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Guarantors and lecturers
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Guarantors:
Doc. Ing. Ondřej Straka, Ph.D. (100%),
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Lecturer:
Doc. Ing. Ondřej Straka, Ph.D. (100%),
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Tutorial lecturer:
Ing. Jiří Ajgl, Ph.D. (100%),
Ing. Jindřich Havlík (100%),
Ing. Jan Krejčí (100%),
Doc. Ing. Ondřej Straka, Ph.D. (100%),
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Literature
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Graduate study programme term essay (40-50)
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45
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Preparation for an examination (30-60)
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50
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Practical training (number of hours)
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26
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Contact hours
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39
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Total
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160
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
disponovat znalostmi z pravděpodobnosti a statistiky |
disponovat znalostmi z oblasti stochastických procesů |
disponovat základními znalostmi z matematiky, fyziky a výpočetní techniky |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
aplikovat základní vztahy pro práci s náhodnými veličinami |
popsat stochastický proces pomocí prvních dvou momentů |
simulovat stochastický systém na počítači |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
N/A |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
disponovat znalostmi základních metod odhadu parametrů |
disponovat znalostmi optimálních metod odhadu náhodných veličin |
disponovat znalostmi základních metod odhadu náhodných procesů |
Skills - skills resulting from the course: |
navrhnout estimátor neznámých parametrů a náhodných veličin |
navrhnout estimátory pro optimální odhad stochastických procesů |
analyzovat estimátory z pohledu vlastností jimi produkovaných odhadů |
aplikovat estimátory na odhad stavu lineárních stochastických dynamických systémů |
Competences - competences resulting from the course: |
N/A |
N/A |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Combined exam |
Skills - skills achieved by taking this course are verified by the following means: |
Seminar work |
Test |
Competences - competence achieved by taking this course are verified by the following means: |
Combined exam |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Skills - the following training methods are used to achieve the required skills: |
Practicum |
Individual study |
Competences - the following training methods are used to achieve the required competences: |
Practicum |
Lecture |
Individual study |
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