Laajuus: 5

Aikataulu: 13.09.2016 - 25.10.2016

Opetusperiodi (voimassa 01.08.2018-31.07.2020): 

I (autumn) 2018 - 2019
I (autumn) 2019 - 2020

Osaamistavoitteet (voimassa 01.08.2018-31.07.2020): 

The student understands the main concepts in stochastics, mathematics and main concepts related to estimation and state estimation, the role of uncertainty in dynamic systems and is able to implement state filtering algorithms both in linear and nonlinear case. The student also can use the tools of stochastic systems identification.

Sisältö (voimassa 01.08.2018-31.07.2020): 

Basics of statistics and stochastic processes. Basic concepts in estimation, ML, MAP, LS, MMSE; unbiased estimators. Linear estimation in static systems. Optimal state estimation in discrete linear dynamic systems, Kalman filter and information filter. Optimal State estimation in nonlinear dynamic systems, recursive functional relationship. Approximation of optimal nonlinear state estimation, particle filter, extended Kalman filters, 1st and 2nd order. Adaptive estimation. Stochastic system identification.

Toteutus, työmuodot ja arvosteluperusteet (voimassa 01.08.2018-31.07.2020): 

Final exam (80%), assignments (20%).

Työmäärä toteutustavoittain (voimassa 01.08.2018-31.07.2020): 

Contact teaching, independent studies and work based-learning, examination

Contact teaching: 6 X 4 +4 x 2 = 32 h
Indepenedent work: 103 h

Oppimateriaali (voimassa 01.08.2018-31.07.2020): 

Yaakov Bar-Shalom, et al: Estimation with applications to tracking and navigation (2001), handouts.

Korvaavuudet (voimassa 01.08.2018-31.07.2020): 

Replaces the course AS-84.3128.

Kurssin kotisivu (voimassa 01.08.2018-31.07.2020): 

https://mycourses.aalto.fi/course/search.php?search=ELEC-E8104

Esitiedot (voimassa 01.08.2018-31.07.2020): 

Basic knowledge of control engineering and robotics, basic probability theory and statistics.

Arvosteluasteikko (voimassa 01.08.2018-31.07.2020): 

0-5

Lisätietoja (voimassa 01.08.2018-31.07.2020): 

language class 3: English

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