kalman

Normally in kalman filter state estimators with dynamics and multiple measurements then the P in the Kalman filter gain is actually the apriori error Covariance matrix.

von Storch et al 2004 in IPCC AR4 « Climate Audit 2007

Normally in kalman filter state estimators with dynamics and multiple measurements then the P in the Kalman filter gain is actually the apriori error Covariance matrix.

von Storch et al 2004 in IPCC AR4 « Climate Audit 2007

It has a lot of ship/submarine specific material I skip over, but the kalman filtering and system identification parts are highly interesting, and the general controls sections apply most to my current project.

Galactic North patternjuggler 2004

It has a lot of ship/submarine specific material I skip over, but the kalman filtering and system identification parts are highly interesting, and the general controls sections apply most to my current project.

Archive 2004-07-31 patternjuggler 2004

Please do not send the messages to me; send them to kalman at history.ucsb.edu.

The Volokh Conspiracy » Closely related law professors and closely related Supreme Court law clerks: 2004

All images are the result of 2 kalman line averages and where appropriate, sequential scans were used to prevent cross talk.

PLoS ONE Alerts: New Articles Chang-Jin Park et al. 2010

All images are the result of 2 kalman line averages and where appropriate, sequential scans were used to prevent cross talk.

PLoS ONE Alerts: New Articles Chang-Jin Park et al. 2010

Its advantage over the kalman filter are essentially its non linearity (of robot state transitions in this case) and its ability to represent multi-modal distributions (which is not the case for kalman where it is assumed to be gaussian).

Random Hacks 2009

Its advantage over the kalman filter are essentially its non linearity (of robot state transitions in this case) and its ability to represent multi-modal distributions (which is not the case for kalman where it is assumed to be gaussian).

Random Hacks 2009

Its advantage over the kalman filter are essentially its non linearity (of robot state transitions in this case) and its ability to represent multi-modal distributions (which is not the case for kalman where it is assumed to be gaussian).

Random Hacks 2009