Comments (4)
I added some links to this tutorial in the docs
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The index page is the basic tutorial. Our discussions in the discourse thread were not really related to the use of this package, they were related to fundamental understanding of how a Kalman filter works and how to model stochastic dynamics, which I assume that a user of this package should already know and is therefore outside of the scope for the documentation of this package. I recommend the book "Statistical Sensor Fusion" by Fredrik Gustafsson.
You might also find this blog post interesting: https://info.juliahub.com/tune-kalman-filter also available as a Pluto notebook https://juliahub.com/pluto/editor.html?id=ad9ecbf9-bf83-45e7-bbe8-d2e5194f2240
from lowlevelparticlefilters.jl.
Very nice tutorial, thanks for sharing!
It took me some time to understand that obs and nonlin are footnotes in the blog post, the square brackets are missing.
from lowlevelparticlefilters.jl.
yeah, the formatting in the notebook unfortunately got a bit butchered when the notebook was translated to a web page :(
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Related Issues (20)
- Typo in DAEUnscentedKalmanFilter docstring
- LowLevelParticleFilters won't compile on Julia 1.8/macOS HOT 4
- Passing dynamics noise density makes stochastic dynamics less expressive HOT 3
- Incremental precomiplation fatally broken HOT 1
- More flexible noise in UKF
- Next major version
- Compatibility to ModelingToolkit.jl? HOT 4
- Observed variables HOT 2
- Installing this package is downgrading many other packages
- Particle filter with second order Markov model HOT 3
- loglik bug for ParticleFilter with resampling
- Does `correct!()` support `missing` samples as explained in docs? HOT 4
- Struct of Arrays and BLAS2->3 optimization HOT 1
- Dependency Deprecated - Yeppp HOT 9
- TagBot trigger issue HOT 32
- notation + documentation HOT 2
- v3.0
- Ensemble Kalman filters? HOT 2
- Support for non-uniform observations? HOT 8
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