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Fixed TOC links.

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I did not update the links to the new appendixes in the last
check in, so they were pointing to the old chapter names.
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Roger Labbe 2015-05-10 20:45:03 -07:00
parent 6d9c500e50
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table_of_contents.ipynb
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@ -110,19 +110,19 @@
"A brief walkthrough of the KalmanFilter class from FilterPy.\n",
"\n",
"\n",
"[**Appendix D: H-Infinity Filters**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/16_HInfinity_Filters.ipynb)\n",
"[**Appendix D: H-Infinity Filters**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Appendix_D_HInfinity_Filters.ipynb)\n",
" \n",
"Describes the $H_\\infty$ filter. \n",
"\n",
"*I have code that implements the filter, but no supporting text yet.*\n",
"\n",
"\n",
"[**Appendix E: Ensemble Kalman Filters**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/17_Ensemble_Kalman_Filters.ipynb)\n",
"[**Appendix E: Ensemble Kalman Filters**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Appendix_E_Ensemble_Kalman_Filters.ipynb)\n",
"\n",
"Discusses the ensemble Kalman Filter, which uses a Monte Carlo approach to deal with very large Kalman filter states in nonlinear systems.\n",
"\n",
"\n",
"[**Appendix F: FilterPy Source Code**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Appendix_D_Filterpy_Code.ipynb)\n",
"[**Appendix F: FilterPy Source Code**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Appendix_F_Filterpy_Code.ipynb)\n",
"\n",
"Listings of important classes from FilterPy that are used in this book.\n",
"\n",