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@@ -11,7 +11,10 @@ There are also libraries for python:
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* [pykalman](https://github.com/pykalman/pykalman).
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## The library
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-In our you can find some **Kalman filter** variants:
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+Technically speaking all filters in YAFL are adaptive since all of them have at least measurement noice covariance adjustment.
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+The term **Adaptive** is used in our docs for **Kalman filter** variants with H-infinity divergence correction.
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+
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+In YAFL you can find these **Kalman filter** variants:
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| Algorithm family | Basic | Adaptive | Robust | Adaptive robust |
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| :--------------- | :----------: | :----------: | :----------: | --------------: |
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@@ -31,23 +34,23 @@ where:
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For all **EKF** variants we have **Bierman** and **Joseph** updates.
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For sequential UD-factorized **UKF** only **Bierman** updates have been implemented.
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-Technically speaking all filters in YAFL are adaptive since all of them have at least measurement noice covariance atadpive adjustment.
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+And yes, we [**can actually**](./doc/UsingEKFTricksWithSPKF.pdf) use **EKF** tricks with **UKF**!
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-### Notes on process and measurement noice covariance adjustments
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+## Notes on process and measurement noice covariance adjustments
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We used [this paper](https://arxiv.org/pdf/1702.00884.pdf) to implement optional Q and R adaptive adjustments.
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Here are som notes on our implementation:
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* All filters in this lib have the optional measurement noice covariance adjustment which can be enabled by setting `rff` to a small positive number e.g. `1e-4`.
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* All EKF filters in this lib have the optional process noice covariance adjustment which can be enabled by setting `qff` to a small positive number e.g. `1e-4`.
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* None of UKF filters have the optional process noice covariance adjustment as it leads to filters instability.
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-And yes, we [**can actually**](./doc/UsingEKFTricksWithSPKF.pdf) use **EKF** tricks with **UKF**!
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-
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+## Notes on implementation
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The library is written in C and is intended for embedded systems usage:
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* We use static memory allocation
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* We use cache-friendly algorithms when available.
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* Regularization techniques are used when necessary. The code is numerically stable.
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* Depends only on C standard library.
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+## Using with C
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To use the library you need to:
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* go to our [Releases page](https://github.com/shkolnick-kun/yafl/releases),
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* download and unpack the latest release source code archive,
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shkolnick-kun