From ce8789213ac035c82eb434812c8226302eaf2fe3 Mon Sep 17 00:00:00 2001 From: rlabbe Date: Fri, 16 May 2014 13:31:02 -0700 Subject: [PATCH] Added Chapter description and links. --- README.md | 22 +++++++++++++++++++--- 1 file changed, 19 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 0ae9bbd..d39eee5 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,7 @@ #[Kalman Filters and Random Signals in Python](http://github.com/rlabbe/Kalman-Filters-and-Random-Signals-in-Python) +### Version 0.0 - not ready for public consumption. In development. + this is a book BLAH BLAH BLAH Contents @@ -7,11 +9,25 @@ Contents * [**Introduction**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-Filters-and-Random-Signals-in-Python/blob/master/Introduction.ipynb) -Introduces stuff + Introduction to the Kalman filter. Explanation of the idea behind this book. -**Chapter 1: You've got me - tells you this and that. and the other thing. +* [**Chapter 1: The g-h Filter**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-Filters-and-Random-Signals-in-Python/blob/master/g-h_filter.ipynb) + Intuitive introduction to the g-h filter, which is a family of filters that includes the Kalman filter. Not filler - once you understand this chapter you will understand the concepts behind the Kalman filter. + + +* [**Chapter 2: The Discrete Bayes Filter**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-Filters-and-Random-Signals-in-Python/blob/master/histogram_filter.ipynb) + Introduces the Discrete Bayes Filter. From this you will learn the probabilistic reasoning that underpins the Kalman filter in an easy to digest form. + +* [**Chapter 3: Gaussian Probabilities**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-Filters-and-Random-Signals-in-Python/blob/master/Gaussians.ipynb) + Introduces using Gaussians to represent beliefs. Gaussians allow us to implement the algorithms used in the Discrete Bayes Filter to work in continuous domains. + +* [**Chapter 4: One Dimensional Kalman Filters**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-Filters-and-Random-Signals-in-Python/blob/master/Kalman_Filters.ipynb) + Implements a Kalman filter by modifying the Discrete Bayesian Filter to use Gaussians. This is a full featured Kalman filter, albeit only useful for 1D problems. + +* [**Chapter 5: Multidimensional Kalman Filter**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-Filters-and-Random-Signals-in-Python/blob/master/Multidimensional_Kalman_Filters.ipynb) + We extend the Kalman filter developed in the previous chapter to the full, generalized filter. + Reading the book -----