Bayesian Filtering and Smoothing D
Aalto University
<p>Statistical modeling and estimation in nonlinear and nonGaussian systems. Bayesian filtering and smoothing theory. Extended Kalman filtering and smoothing, sigma point and unscented filtering and smoothing, sequential Monte Carlo particle filtering and smoothing. Adaptive nonlinear filtering; ML, MAP, MCMC, and EM estimation of system parameters. Example applications from navigation, remote surveillance, and time series analysis.</p>
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Course dates
08 January 2026 - 13 April 2026
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Course organizer
Ville Kyrki, Simo Särkkä
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Place/Venue
School of Electrical Engineering / Department of Electrical Engineering and Automation
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City
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Country
Finland
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Workload
5
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Link
https://mycourses.aalto.fi/course/search.php?...
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