probml / pyprobml

Python code for "Probabilistic Machine learning" book by Kevin Murphy

MIT License

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Add ekf_vs_ukf.ipynb #1018

Closed petergchang closed 2 years ago

petergchang commented 2 years ago

Description

A notebook that demonstrates the UKF's capacity to approximate the target distribution that results from a non-linear transformation with greater accuracy than the EKF. This is because while the EKF approximates the distribution locally at the mean, the UKF utilizes the distribution of the sigma points to more accurately capture the global distribution.

Figure Number

Adapts (with slightly different non-linear transformation) Sarkka's Figures 5.3, 5.4, and 5.5.

Figures

Issue

1017

Checklist

[x] Performed a self-review of the code
[x] Tested on Google Colab.

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