daviddoji/Kalman-and-Bayesian-Filters-in-Python
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Start of the Smoothin chapter. RTS implemented.

Browse Source
This commit is contained in:
Roger Labbe
2014-11-16 15:54:28 -08:00
parent 3367806b07
commit 75c4e9ce97
3 changed files with 570 additions and 4 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
README.md
View File

@@ -146,7 +146,7 @@ EKF and UKF are linear approximations of nonlinear problems. Unless programmed c
* [**Chapter 13: Numerical Stability**](not implemented)
* [**Chapter 14: Smoothing**](not implemented)
* [**Chapter 14: Smoothing**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/14_Smoothing/14_Smoothing.ipynb)
Kalman filters are recursive, and thus very suitable for real time filtering. However, they work well for post-processing data. We discuss some common approaches.