Moved chapter 10 for reorg

10_Unscented_Kalman_Filter.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:d06fb32e6aee455bb9d541df8972b8f773a454b227d9a76a72d950bc93a76084"
+  "signature": "sha256:66e7c1ac6733ab9cc3c8a71c3a2a0dc29d1b3123baa0531c902b83527076bbf3"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -32,7 +32,7 @@
       "from __future__ import division, print_function\n",
       "import matplotlib.pyplot as plt\n",
       "import sys\n",
-      "sys.path.insert(0,'../code') # allow us to format the book\n",
+      "sys.path.insert(0,'./code') # allow us to format the book\n",
       "import book_format\n",
       "book_format.load_style()"
      ],
@@ -261,7 +261,7 @@
        "output_type": "pyout",
        "prompt_number": 1,
        "text": [
-        "<IPython.core.display.HTML at 0x7f7386ca0198>"
+        "<IPython.core.display.HTML at 0x7f3a3b77a400>"
        ]
       }
      ],
@@ -309,9 +309,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAxIAAAGNCAYAAACFa0d0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAxoAAAGGCAYAAAD8e/dDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736ddddeb8>"
+        "<matplotlib.figure.Figure at 0x7f3a1e8dd0f0>"
        ]
       }
      ],
@@ -347,9 +347,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAxgAAAGaCAYAAACMmuWeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAxgAAAGaCAYAAACMmuWeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736dddd2b0>"
+        "<matplotlib.figure.Figure at 0x7f3a1e8d94a8>"
        ]
       }
      ],
@@ -396,7 +396,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAv4AAAF0CAYAAABbpj2aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736e0c4cf8>"
+        "<matplotlib.figure.Figure at 0x7f3a1ebbdf28>"
        ]
       }
      ],
@@ -514,16 +514,16 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736de0cef0>"
+        "<matplotlib.figure.Figure at 0x7f3a1e8ff5c0>"
        ]
       },
       {
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "Difference in mean x=-0.009, y=43.177\n"
+        "Difference in mean x=0.074, y=43.423\n"
        ]
       }
      ],
@@ -575,7 +575,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAyoAAAGNCAYAAAD+T4W4AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736dc83400>"
+        "<matplotlib.figure.Figure at 0x7f3a1e778588>"
        ]
       }
      ],
@@ -615,7 +615,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAv4AAAF0CAYAAABbpj2aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3WlwHGWeJvAn61KVVKpUqUpXSfIh2ZYPbIMvbGwDNtiY\nwxjUDRiGpnFPT/d2z+zQXzZ2JmI/zLfdjf3S3Tvb19IN2wxgTCOmwbhpGxsMvm9s4wtLsq37qEtS\nqUqqqsz9UBbY40tHVr1Zlc8voiM6RDh4hCvz/9SbmW9KqqqqICIiIiKinGYSHYCIiIiIiNKPxZ+I\niIiIyABY/ImIiIiIDIDFn4iIiIjIACy3+gfhcDiTOYiIiIiISCOyLN/wM674ExEREREZAIs/ERER\nEZEB3PJWn2vd7FIBERERERHpx51u1eeKPxERERGRAbD4ExEREREZAIs/EREREZEBsPgTERERERkA\niz8RERERkQGw+BMRERERGQCLPxERERGRAbD4ExEREREZAIs/EREREZEBsPgTERERERkAiz8RERER\nkQGw+BMRERERGQCLPxERERGRAbD4ExEREREZAIs/EREREZEBsPgTERERERkAiz8RERERkQGw+BMR\nERERGQCLPxERERGRAbD4ExEREREZAIs/EREREZEBsPgTERERERkAiz8RERERkQGw+BMRERERGQCL\nPxERERGRAbD4ExEREREZAIs/EREREZEBsPgTERERERkAiz8RERERkQGw+BMRERERGQCLPxERERGR\nAbD4ExEREREZAIs/EREREZEBsPgTERERERkAiz8RERERkQGw+BMRERERGQCLPxERERGRAbD4ExER\nEREZAIs/EREREZEBsPgTERERERkAiz8RERERkQGw+BMRERERGQCLPxERERGRAbD4ExEREREZAIs/\nEREREZEBsPgTERERERkAiz8RERERkQGw+BMRERERGQCLPxERERGRAbD4ExEREREZAIs/EREREZEB\nsPgTERERERkAiz8RERERkQGw+BMRERERGQCLPxERERGRAbD4ExEREREZAIs/EREREZEBsPgTERER\nERkAiz8RERERkQGw+BMRERERGQCLPxERERGRAbD4ExEREREZAIs/EREREZEBWEQHoNyTTCYRDAbh\n9/vh9/vR2urHwMAQhocTiMeTSCYVmM0mWK1mWK1mOJ15qKrywONJ/c/tdsNi4UeTaLxUVUU0Gv3m\nGOzu9qOjI/zNMZhIJKGqKqxWyzfHYVmZC2Vl3x6HBQUFkCRJ9K9ClLXGMwsrK4vh8Xjg9Xo5Cykt\n+ImiCUkkEmhubsb58024dKkXra1+9PT0QVVdkCQPFMUDi6UcVqsDkmSGyWSGJJmgqgoUJQlVTSKR\niCEeD0CSLgPwAwijpKQQlZUeTJ7sQV3dVNTU1MBms4n+dYl0KRAI4Pz5C2hs7MCVK360tfkRiagw\nm71QVQ9U1YO8vFqYzdZvjkMA3xyDipLA0FAYwBVI0nEoih92exI+nwfV1R5Mm1aOuroZ8Hq9/DJA\ndBNazkKTqQWq2gsgDK+3EFVVnIWkHUlVVfVm/yAcDn/z/2VZzlgg0r+BgQFcuHABR45cwLFjzRge\nLockTYPDUYr8fA/sdvc3xWI8FCWJWCyEaNSPwcEeqOpFmM1tuPvuyViyZAZmzJjBzyQZmqIoaGlp\nwVdfXcD+/efR2hoDMAM2WzXy8z1wODywWvMnVNLj8UFEowEMDvoxNNQC4ALKyy24774ZmDNnBiZP\nngyzefzHOVG2u3EWlgGYhvz8srTMQkW5CIuFs5Bu7079ncWfRiUUCuHYsS9x4MAFXLzoh6rWwm6v\nQ3HxNFit+Wn/9ycSMQQCFxGNXgBwEVOnunDffXW455558Hg8af/3E4mmKAouXLiAw4fP4NChi4hE\nXABmoKioDoWFvrSvxKuqikikC4HAeQAXYLf7sXhxLRYvnoVZs2bxSwAZQigUwvHjJ7F//3mBs7AR\n0eh5jMzCZctmYMGC+ZyFBIDFnyaoo6MDO3bsxe7djVCUeXC5ZkKWJ01oFWOiVFVBONyCcPg8gBNY\nvnwSHnlkOaqrq4VlIkqX4eFhHD9+Av/+7/vR0eGE1ToPHs8M2O1iz8vDwwPw+y9gePg0PJ5ebNhw\nLxYvXgi73S40F1E6pGbhPuzefRHJ5FzI8kzI8mThs7CvrxWh0DlI0pe4775qrF17HyZNmiQsE4nH\n4k9jpqoqGhsbsW3bXhw75ofFshTl5QthseSJjnaDZHIYnZ0nMDy8H3PnOvH44/ehrq4OJhM3rKLs\nFolEsG/fIXz44RH09U2C230fZFmfX277+zvg9+9Dfv5FPPbYPbj//qVwuVyiYxFNyLezcB+OHeu9\nOgsXwGLR35fbZDKOrq4TGBrax1locCz+NGrJZBKnTp3Cn/+8D01NEhyO+1BaepfQFY3RUlUFPT1n\nEYnsQ3V1DBs2LMM999zNHREo6/j9fnz66T5s3/4V4vG7UFKyDPn52XEJPxYLoavrAMzmL7F69Qw8\n9NB9KCsrEx2LaEySySROnz59dRYCdnt2zcLe3nMYGNjLWWhQLP40Ki0tLfh//28rvv7aAVleAbe7\nNit371BVFeHwFQSDe1Bd7ccPfvAEampqRMciuqN4PI5PPtmN9947BlVdjLKyJbDZCkTHGpd4PIqu\nrqNQlANYv342Hn10NW8BoqyQq7Nw06bHUVtbKzoWZQCLP91WNBrFRx99gq1bLyA//xGUlMzJypPc\nzfj9F9DXtw1r107Chg1r4XQ6RUciuqmvv/4ar722DW1tlaisXAebLTc+q/F4FG1tO+DxfI0f/GAd\nZs+enTPnF8ot0WgU27btxNat5+Fw5OYsfPjhajz99COchTmOxZ9uSlVVnDx5Cq+9th3h8CxUVj6k\ny/sWJyqZHEZb22coKPgS3//+aixcuCBnTuaU/fr7+9HQ8DF27mxHUdHjKC6eJjpSWoTDVxAIbMWy\nZTKee+4xuN1u0ZGIAKRm4alTp/H669sRDM7M8Vm4G/n5x/HSS6uxePFCzsIcxeJPN/D7/Xj77Y9w\n6NAgvN4n4HJViY6UdgMDneju3or58yW8+OITvO+YhFIUBYcOHcEbb3yGWGwRfL6VMJutomOllaIk\n0dGxHybTPjz//H1YuXIZtwAloQKBAN5++yMcPDgAr3e9QWZh19VZCM7CHMXiT9c5evQ4fve7HVCU\nlfD57oUkGeeJf1VV0dl5FMnkLmzadD/uu+9ernhQxg0MDODVV9/FsWNAWdkTKCgoER0po6LRIDo6\ntmH27AH8p//0HIqKikRHIgM6fvwEfvOb7VCUFaiouDcrHtzVSmoWHkMyuQsvv7wCy5cv5SzMISz+\nBCC1S8Gf//wx3n+/CeXlGw1XNq4Vi4XQ1rYZ69aV4tln18Nqze2VVtKPtrY2/PKXW+D3343KygcN\nO2xVVUV7+wEUFOzFK698B1OnThUdiQwimUzigw/+ivffb0RZGWchZ2HuYfEnDAwM4P/+3y04ftyO\nSZPqc/L+xbFKJuO4cuUDzJrVi5/8ZCM/45R2x44dx69/vQN5eU/C650pOo4uBINN6O9vwN/+7Qpe\ngaO0+/ZqWx5n4VUjs3DmzF785Ce8ApcLWPwNrq2tDb/4xTvw++9BVZVxVxhvJrXquB8FBfvws599\nF1OmTBEdiXLQyApjQ0Oj4a+23QxXHSkTRq629fbOR1XVKs7Ca/AKXG5h8TcwrjCODlcdKV24wjg6\nvAJH6XT8+An86lfbYbOtR0nJLNFxdCsYbEZ//3uchVmOxd+AVFXFtm2fYPPmc1xhHKXUA4fvYP36\nSnz3u0/whEcT1tvbi//1v94w/P38ozVyBc7p3If/8l9egM/nEx2JstzILHznnXOGv59/tEauwK1f\n78N3v/sETCbjbACSK1j8DUZVVWzduh1btlzGpEnfg9XqEB0paySTw7h06S088YQbzz77JIsajVtv\nby/+x//4IyKR1Sgru1t0nKzS23sOkvQh/vmf/4bln8ZNVVV89NEOvPNOMyZNeomzcAxSs/BtPPaY\njOeee5LlP8vcqb/zbzOHsPRPjNlsw5QpL2Dr1iC2bPkAt/hOTHRbLP0T4/XOhKqux3//72+ivb1d\ndBzKQiz9E5Oahc9j27Yw3nnnAyiKIjoSaYjFP0ew9GuD5Z8mgqVfGyz/NF4s/dpg+c9dLP45gKVf\nWyz/NB4s/dpi+aexYunXFst/bmLxz3Is/enB8k9jwdKfHiz/NFos/enB8p97WPyz3LZtn7D0p8m1\n5f/ddz9k+aebCgaD+J//k6U/Xa4t/11dXaLjkE795S87WfrT5Nryz1mY/Vj8s9ixY8exefNZlv40\nGin/H37Yjr17D4iOQzozNDSE//N/3kY4vJylP4283plIJtfhl7/cjMHBQdFxSGeOHz+BzZvPcBam\n0Uj537q1E198sV90HJoAFv8s1drail//egfKy5/niS7NzGYbKis34ve/34vGxkbRcUgnVFXFW2/9\nOy5erEJFxRLRcXJeaelcdHbOwe9//y6SyaToOKQTra2t+NWvtqOsbCOs1nzRcXLayCx87bV9uHjx\noug4NE4s/lmov78fP//5FuTlbeALSTLEbi+CLD+Dn/+8AYFAQHQc0oGdO3dj164BTJr0GN/5kCFV\nVatx+LAFH364XXQU0oH+/n784hdbkJf3JAoKSkXHMQS7XYYsP4Nf/OJ9+P1+0XFoHFj8s0wikcBv\nfrMZodBieL11ouMYSlHRZAwPr8L//t9vY2hoSHQcEujs2bN4443jqK5+DiaTRXQcw5AkEyZN+g4a\nGhpx5Mgx0XFIoEQigd/+9h0Eg4vg9c4UHcdQioomIx5fjX/9182chVmIxT+LqKqKd9/ditLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f73606337f0>"
+        "<matplotlib.figure.Figure at 0x7f3a15160470>"
        ]
       }
      ],
@@ -670,7 +670,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAxQAAAGNCAYAAACIdTczAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736dc78f98>"
+        "<matplotlib.figure.Figure at 0x7f3a19b63630>"
        ]
       }
      ],
@@ -1081,9 +1081,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAzkAAAGkCAYAAAASdeutAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAzkAAAGkCAYAAAASdeutAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736063e198>"
+        "<matplotlib.figure.Figure at 0x7f3a151354e0>"
        ]
       }
      ],
@@ -1113,9 +1113,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAswAAAKNCAYAAAA01T3TAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAssAAAKNCAYAAADWCSaqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736059e0b8>"
+        "<matplotlib.figure.Figure at 0x7f3a1e756da0>"
        ]
       }
      ],
@@ -1161,7 +1161,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAp4AAAJ2CAYAAAD2YYJ8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f73605a5b38>"
+        "<matplotlib.figure.Figure at 0x7f3a169d4cc0>"
        ]
       }
      ],
@@ -1284,7 +1284,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAqkAAAJ9CAYAAAAWiev+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f73605f1400>"
+        "<matplotlib.figure.Figure at 0x7f3a151131d0>"
        ]
       }
      ],
@@ -1316,7 +1316,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAsYAAAJ9CAYAAAA2ZbQDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736dd81710>"
+        "<matplotlib.figure.Figure at 0x7f3a1f6ec0f0>"
        ]
       }
      ],
@@ -1416,7 +1416,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAArQAAAJ2CAYAAACuHhFlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f7361ecd0f0>"
+        "<matplotlib.figure.Figure at 0x7f3a1698b8d0>"
        ]
       }
      ],
@@ -1467,7 +1467,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAArQAAAJ2CAYAAACuHhFlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736dc1fe80>"
+        "<matplotlib.figure.Figure at 0x7f3a1e863630>"
        ]
       }
      ],
@@ -1542,7 +1542,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAArQAAAJ2CAYAAACuHhFlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736055c780>"
+        "<matplotlib.figure.Figure at 0x7f3a1e7c8a90>"
        ]
       }
      ],
@@ -1663,7 +1663,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAp0AAAJ9CAYAAAB3kcm8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f7361f43d30>"
+        "<matplotlib.figure.Figure at 0x7f3a1509e8d0>"
        ]
       }
      ],
@@ -1734,7 +1734,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAApMAAAJ8CAYAAACiBCqqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f7361eebc50>"
+        "<matplotlib.figure.Figure at 0x7f3a16a3ff98>"
        ]
       }
      ],
@@ -1834,7 +1834,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAowAAAJ2CAYAAADVOtOpAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736dbabb70>"
+        "<matplotlib.figure.Figure at 0x7f3a169ba940>"
        ]
       }
      ],
@@ -1869,7 +1869,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAo8AAAJ2CAYAAAA+DWiqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f7360587d68>"
+        "<matplotlib.figure.Figure at 0x7f3a150afeb8>"
        ]
       }
      ],
@@ -1981,7 +1981,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAqsAAAJ2CAYAAAB4u8sAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f7361ecd3c8>"
+        "<matplotlib.figure.Figure at 0x7f3a1e8b31d0>"
        ]
       },
       {
@@ -2753,7 +2753,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAoAAAAJ3CAYAAAAEWuCCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736db2c4e0>"
+        "<matplotlib.figure.Figure at 0x7f3a1e621390>"
        ]
       }
      ],
@@ -2871,7 +2871,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAsUAAAKUCAYAAADsGUVKAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736dc7f358>"
+        "<matplotlib.figure.Figure at 0x7f3a1e80a3c8>"
        ]
       }
      ],
@@ -2981,7 +2981,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAsUAAAKUCAYAAADsGUVKAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736de0c320>"
+        "<matplotlib.figure.Figure at 0x7f3a1514a2b0>"
        ]
       }
      ],
@@ -3045,7 +3045,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAsAAAAKUCAYAAAAKMI4OAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f736056cb00>"
+        "<matplotlib.figure.Figure at 0x7f3a1e60c6a0>"
        ]
       }
      ],

10_Unscented_Kalman_Filters/README.md

@@ -1,2 +0,0 @@
-You may read this book online via nbviewer by using this link:
-[*Read Online Now*](http://nbviewer.ipython.org/github/rlabbe/Kalman-and-Bayesian-Filters-in-Python/blob/master/table_of_contents.ipynb)