diff --git a/toc.ipynb b/toc.ipynb
index ebd461c..bb7657a 100644
--- a/toc.ipynb
+++ b/toc.ipynb
@@ -1,7 +1,7 @@
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@@ -69,12 +69,12 @@
       "Building on material in Chapter 5, walks you through the design of several Kalman filters. Discusses, but does not solve issues like numerical stability.\n",
       "    \n",
       "\n",
-      "[**Chapter 8: Extended Kalman Filters**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Extended-Kalman-Filters.ipynb)\n",
+      "[**Chapter 8: Extended Kalman Filters**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Extended_Kalman_Filters.ipynb)\n",
       "    \n",
       "Kalman filter as covered only work for linear problems. Extended Kalman filters (EKF) are the most common approach to linearizing non-linear problems.\n",
       "\n",
       "\n",
-      "[**Chapter 9: Unscented Kalman Filters**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Unscented-Kalman-Filter.ipynb)\n",
+      "[**Chapter 9: Unscented Kalman Filters**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Unscented_Kalman_Filter.ipynb)\n",
       "    \n",
       "Unscented Kalman filters (UKF) are a recent development in Kalman filter theory. They allow you to filter nonlinear problems without requiring a closed form solution like the Extended Kalman filter requires.\n",
       "\n",