Computer control and estimation algorithms including deterministic and stochastic models. Markov sequence and Bayes decision rules, linear Kalman filtering, predicting, and smoothing. Parameter identification, combined state and parameter estimation. Adaptive filters and on-line rapid estimation schemes, extended and nonlinear filters. Optimal digital control of deterministic and stochastic systems. Separation theorems.
Spring | Summer | Fall | ||
---|---|---|---|---|
(Session 1) | (Session 2) | |||
2023 | ||||
2022 | ||||
2021 | ||||
2020 | ||||
2019 | ||||
2018 | ||||
2017 | ||||
2016 | ||||
2015 | ||||
2014 | ||||
2013 | ||||
2012 | ||||
2011 | ||||
2010 | ||||
2009 | ||||
2008 | ||||
2007 | ||||
2006 | ||||
2005 | ||||
2004 | ||||
2003 | ||||
2002 | ||||
2001 | ||||
2000 | ||||
1999 | ||||
1998 |