diff --git a/10_Unscented_Kalman_Filters/Unscented_Kalman_Filter.ipynb b/10_Unscented_Kalman_Filters/Unscented_Kalman_Filter.ipynb
index 0e171b1..7dfd782 100644
--- a/10_Unscented_Kalman_Filters/Unscented_Kalman_Filter.ipynb
+++ b/10_Unscented_Kalman_Filters/Unscented_Kalman_Filter.ipynb
@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:f5a2f8a7d4867ab480fb52dfb55fb1ec1d2af047553722cbbb8df2c6dc7bd817"
+  "signature": "sha256:ce14fff7e0ef1785ba83a455e926d8748b9cbd6b084e913d3580ea41d79d0221"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -1815,7 +1815,7 @@
       "\\Sigma = SS^\\mathsf{T} \\\\\n",
       "$$\n",
       "\n",
-      "This latter method is typically chosen in computational linear algebra because this expression is easy to compute using something called the *Cholesky decomposition*. \n",
+      "This latter method is typically chosen in computational linear algebra because this expression is easy to compute using something called the *Cholesky decomposition* [3]. \n",
       "Numpy provides this with the `numpy.linalg.cholesky()` method. If your language of choice is Fortran, C, C++, or the like standard libraries such as LAPACK also provide this routine. And, of course, matlab provides `chol()`, which does the same thing.\n",
       "\n",
       "This method returns a lower triangular matrix, so we will take the transpose of it so that in our for loop we can access it row-wise as `U[i]`, rather than the more cumbersome column-wise notation `U[i,:]`.\n",
@@ -2401,7 +2401,9 @@
       "\n",
       "- [1] Simon, Dan. *Optimal State Estimation*, John Wiley & Sons, 2006.\n",
       "\n",
-      "- [2] Julier, Simon J.; Uhlmann, Jeffrey \"A New Extension of the Kalman  Filter to Nonlinear Systems\". Proc. SPIE 3068, Signal Processing, Sensor Fusion, and Target Recognition VI, 182 (July 28, 1997)"
+      "- [2] Julier, Simon J.; Uhlmann, Jeffrey \"A New Extension of the Kalman  Filter to Nonlinear Systems\". Proc. SPIE 3068, Signal Processing, Sensor Fusion, and Target Recognition VI, 182 (July 28, 1997)\n",
+      "\n",
+      "- [3] Cholesky decomposition. Wikipedia. http://en.wikipedia.org/wiki/Cholesky_decomposition"
      ]
     }
    ],