From dd8a0b72f6da1b2e06c113140de506a3cb91a16e Mon Sep 17 00:00:00 2001 From: Roger Labbe Date: Sun, 30 Nov 2014 16:41:52 -0800 Subject: [PATCH] Fixed link to HInifnity chapter. --- README.md | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index d70053b..9393952 100644 --- a/README.md +++ b/README.md @@ -140,11 +140,13 @@ Unscented Kalman filters (UKF) are a recent development in Kalman filter theory. EKF and UKF are linear approximations of nonlinear problems. Unless programmed carefully, they are not numerically stable. We discuss some common approaches to this problem. -* [**Chapter 12: H-Infinity Filters**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/12_HInfinity_Filters/HInfinity_Filter.ipynb) +* [**Chapter 12: H-Infinity Filters**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/12_HInfinity_Filters/HInfinity_Filters.ipynb) * [**Chapter 13: Numerical Stability**](not implemented) +Not written yet. + * [**Chapter 14: Smoothing**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/14_Smoothing/Smoothing.ipynb) @@ -153,12 +155,12 @@ Kalman filters are recursive, and thus very suitable for real time filtering. Ho * [**Chapter 15: Particle Filters**](not implemented) -Particle filters uses a Monte Carlo technique to +Not written yet * [**Chapter 16: Multihypothesis Tracking**](not implemented) -description +Not written yet. * [**Appendix: Installation, Python, NumPy, and FilterPy**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Appendix_A_Installation/Appendix_Installation.ipynb)