This course introduces the Kalman filter as a method that can solve problems related to estimating the hidden internal state of a dynamic system. It develops the background theoretical topics in state ...

As a follow-on course to "Kalman Filter Boot Camp", this course derives the steps of the linear Kalman filter to give understanding regarding how to adjust the method to applications that violate the ...

Aki Tsuruta defends her doctoral thesis "Application of the Ensemble Kalman filter in the estimation of global methane balance" on Thursday, 21 December 2017 at 12 o'clock in the Auditorium Brainstorm ...

The problem of nonlinear filtering is studied asymptotically as the noise tends to zero. Detectability conditions ensuring that the filtering error tends to zero are ...

Data truncation is a commonly accepted method of dealing with initialization bias in discrete-event simulation. An algorithm for determining the appropriate initial-data truncation point for ...