Added text explaining FPF' example.

Interactions.ipynb

@@ -36,23 +36,33 @@
     "# Experimenting with FPF'\n",
     "\n",
     "\n",
-    "The Kaman filter uses the equation $x^- = FPF^\\mathsf{T}$.\n",
+    "The Kaman filter uses the equation $P^- = FPF^\\mathsf{T}$ to compute the prior of the covariance matrix during the prediction step, where P is the covariannce matrix and F is the system transistion function. For a Newtonian system $x = \\dot{x}\\Delta t + x_0$ F might look like\n",
     "\n",
-    "**blah**"
+    "$$F = \\begin{bmatrix}1 & \\Delta t\\\\0 1\\end{bmatrix}$$\n",
+    "\n",
+    "$FPF^\\mathsf{T}$ alters P by taking the correlation between the position ($x$) and velocity ($\\dot{x}). This interactive plot lets you see the effect of different designs of F has on this value. For example,\n",
+    "\n",
+    "* what if $x$ is not correlated to $\\dot{x}$? (set F01 to 0)\n",
+    "\n",
+    "* what if $x = 2\\dot{x}\\Delta t + x_0$? (set F01 to 2)\n",
+    "\n",
+    "*  what if $x = \\dot{x}\\Delta t + 2*x_0$? (set F00 to 2)\n",
+    "\n",
+    "* what if $x = \\dot{x}\\Delta t$?  (set F00 to 0)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc9eb8>"
+       "<matplotlib.figure.Figure at 0x7e73630>"
       ]
      },
      "metadata": {},