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by starchild_3001
1415 days ago
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To me the biggest magic of kalman filtering wasn't the low-pass nature (yes it's a multidimensional low pass filter!), but rather issues around system identification. Namely if and when the system equations evolve as much as the hidden state, then things get really interesting! That specific formulation (joint system estimation + Kalman smoothing) was fairly interesting and useful for the applications I worked on. Obviously your mileage may vary :) As an addendum, I want to say a well designed whitening matrix + IIR filter can replace a Kalman filter, again depending on the application. Just makes things easier to understand, debug etc. Works if your vector is somehow decomposable into roughly independent scalars. |
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