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Course Catalog 2010-2011
MAT-55216 Topics in applied mathematics, 3 cr
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Lessons
Study type | P1 | P2 | P3 | P4 | Summer | Lecture times and places |
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Description:
Bayesian estimation of discrete-time processes (5 credits): Modeling of time-varying systems with uncertainty, optimal filtering and optimal smoothing, linear and nonlinear Kalman filters (EKF/UKF/SLF), linear and non-linear Rauch-Tung-Striebel smoothers, sequential Monte Carlo methods, particle filters and smoothers. Example applications from navigation, remote surveillance and time series analysis.
Person responsible:
Robert Piche
Target groups:
3.-n. vuosikurssi
DI-Opiskelijat
International Students
Jatko-opiskelijat
Teknis-luonnontieteellinen koulutusohjelma
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Additional information of course implementation:
Prerequisites: Multivariate calculus, matrix algebra, basic probability and estimation (e.g. one of the TUT courses Bayesian Methods, Stochastic Processes, or Mathematics for Positioning); Matlab/Octave