Steady-state Kalman Predictor: Examples and Comparison

In course

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Description

This lecture covers the steady-state Kalman predictor, including its convergence properties and error characteristics. Examples are provided to illustrate the application of the Kalman filter in noisy settings. A comparison between Luenberger and Kalman filtering is discussed.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_m09iv2fx

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Ontological neighbourhood

Information engineering

Control theory and engineering: Control theory

Statistics

Statistical inference: Mathematical statistics

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