Proof reading Chapter 12

- Fixed some typos
- Commented issue https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/issues/395

12-Particle-Filters.ipynb

@@ -81,7 +81,7 @@
     "\n",
     "* **multivariate**: we want to track several attributes, such as position, velocity, turn rates, etc.\n",
     "\n",
-    "* **unknown process model**: we may not know the process model of the system\n",
+    "* **unknown process model**: we may not know the process model of the system.\n",
     "\n",
     "None of the filters we have learned work well with all of these constraints. \n",
     "\n",
@@ -110,7 +110,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -180,7 +180,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -271,7 +271,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -323,7 +323,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -355,7 +355,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -548,7 +548,7 @@
     "\n",
     "$$\\displaystyle \\mu = \\frac{1}{N}\\sum_{i=1}^N w^ix^i$$\n",
     "\n",
-    "Here I adopt the notation $x^i$ to indicate the $\\mathtt{i}^{th}$ particle. A superscript is used because we often need to use subscripts to denote time steps the $\\mathtt{k}^{th}$ or $\\mathtt{k+1}^{th}$ particle, yielding the unwieldy $x^i_{k+1}$. \n",
+    "Here I adopt the notation $x^i$ to indicate the $\\mathtt{i}^{th}$ particle. A superscript is used because we often need to use subscripts to denote time steps, yielding the unwieldy $x^i_{k+1}$ for the $\\mathtt{k+1}^{th}$ time step for example. \n",
     "\n",
     "This function computes both the mean and variance of the particles:"
    ]
@@ -702,7 +702,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -831,7 +831,7 @@
     },
     {
      "data": {
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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -886,7 +886,7 @@
     },
     {
      "data": {
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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -936,7 +936,7 @@
     },
     {
      "data": {
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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -974,7 +974,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1029,7 +1029,7 @@
     "\n",
     "$q(x)$ is known to us, so we can compute $\\int f(x)q(x)$ using MC integration. That leaves us with  $\\pi(x)/q(x)$.  That is a ratio, and we define it as a *weight*. This gives us\n",
     "\n",
-    "$$\\mathbb{E}\\big[f(x)\\big] = \\sum\\limits_{i=1}^N f(x^i)w(x^i)$$\n",
+    "$$\\mathbb{E}\\big[f(x)\\big] = \\sum\\limits_{i=1}^N f(x^i)q(x^i)w(x^i)$$\n",
     "\n",
     "Maybe that seems a little abstract. If we want to compute the mean of the particles we would compute\n",
     "\n",
@@ -1104,7 +1104,7 @@
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1156,7 +1156,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1238,7 +1238,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAz4AAABkCAYAAABHNuXUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAA9hAAAPYQGoP6dpAAASVElEQVR4nO3de1CU9QLG8WcVFnZR7gbeUgK8YAo2TeeUJanD6SKWFt0YtSzH0hxTco4e81LWdDqeU55uhGfIsJRqmrxkNTVdiKmZbDJNmylKOspBDUpIwBQX9Hf+2NhaAVkQ2OXt+5nxj/3x2/d99nVd3sd9LzZjjBEAAAAAWFgvfwcAAAAAgK5G8QEAAABgeRQfAAAAAJZH8QEAAABgeRQfAAAAAJZH8QEAAABgeRQfAAAAAJZH8QEAAABgeRQfAAAAAJZH8QGAADV06FDdcccdbc776KOPZLPZ9NFHHwVEnj+qlv4eHnzwQdlsNv+FAgB4BPk7AACgZVu2bFF4eLi/Y+AczJ49W1dffbW/YwAARPEBgE5x/PhxOZ3OTl3m2LFjO3V5/mKMUX19vRwOh7+jdLtBgwZp0KBB/o4BABCHugFAuzUdvrRr1y5lZWUpKipKiYmJktw7+bm5uUpLS5PD4VBUVJSysrL03//+12sZu3fvVmZmps477zyFhIRowIABmjx5sg4ePOiZ09KhZSUlJbr66qvldDoVGxure+65R3V1dc0ytnZY2pVXXqkrr7zS87i+vl7333+/0tLSFBERoejoaF166aXatm1bh7ePzWbT/PnzlZeXp5EjRyokJEQbNmyQJO3bt0/Z2dme1z1y5Eg9++yzXs8/ffq0HnnkEQ0fPlwOh0ORkZEaM2aMnnzySc+c0tJSzZo1S8nJyXI6nRo4cKCmTJmir776ymtZTYefFRYWasmSJerfv7/69OmjKVOmqLKyUnV1dZozZ45iY2MVGxurWbNm6dixYy2+nnXr1mnYsGEKCQlRSkqKXnnllTa3RUuHug0dOlSZmZl65513dNFFF8nhcGjEiBFav359s+d/8sknuvTSSxUaGqqBAwdqxYoVys/Pl81m04EDB9pcPwDgN3zjAwAddMMNN+jWW2/VPffco19++UWSdPfdd6ugoEALFizQP/7xD1VXV2v16tW67LLLtGfPHsXFxemXX35RRkaGEhIS9OyzzyouLk4VFRUqKipqscQ0qaysVHp6uoKDg5Wbm6u4uDht2rRJ8+fP7/BrOHnypKqrq7V48WINHDhQLpdL77//vm644Qa98MILmjlzZoeWu3XrVn388cdauXKl4uPjdd555+nrr7/WZZddpvPPP1+PP/644uPj9e6772rBggU6cuSIVq1aJUlas2aNHnzwQS1fvlzjx49XQ0ODSkpKdPToUc/yDx8+rJiYGD322GPq16+fqqurtWHDBv3pT3/S7t27NXz4cK88y5Yt04QJE1RQUKADBw5o8eLFuu222xQUFKTU1FS9/PLL2r17t5YtW6a+ffvqqaee8nr+G2+8oaKiIq1evVphYWHKzc31PD8rK6vd22fPnj26//77tXTpUsXFxSk/P1933XWXkpKSNH78eEnS3r17lZGRoWHDhmnDhg1yOp3Ky8vTxo0b270+AIAkAwBol1WrVhlJZuXKlV7jn376qZFkHn/8ca/x8vJy43A4zF//+ldjjDE7d+40kszWrVvPup4hQ4aY22+/3fN4yZIlxmazmS+//NJrXkZGhpFkioqKWn1uk/T0dJOent7qOhsbG01DQ4O56667zNixY8+apzWSTEREhKmurvYav+qqq8ygQYNMTU2N1/j8+fNNaGioZ35mZqZJS0trcz1n5na5XCY5OdksWrTIM15UVGQkmSlTpnjNX7hwoZFkFixY4DU+depUEx0d3ez1OBwOU1FR4bW+ESNGmKSkpGbr+v3fQ9N75feGDBliQkNDTVlZmWfsxIkTJjo62tx9992esZtuusmEhYWZn376yTN26tQpk5KSYiSZ/fv3+7BlAABNONQNADroxhtv9Hr85ptvymazafr06WpsbPT8iY+PV2pqqudqX0lJSYqKitKSJUuUl5enr7/+2qf1FRUVadSoUUpNTfUaz87OPqfX8dprr2ncuHHq06ePgoKCFBwcrOeff17ffPNNh5c5ceJERUVFeR7X19frgw8+0LRp0+R0Or22z7XXXqv6+nrt2LFDknTJJZdoz549mjdvnt59913V1tY2W35jY6MeffRRpaSkyG63KygoSHa7Xfv27Wsxd2ZmptfjkSNHSpImT57cbLy6urrZ4W6TJk1SXFyc53Hv3r11yy23qLS01OvwRF+lpaXp/PPP9zwODQ3VsGHDVFZW5hkrLi7WxIkTFRsb6xnr1auXbr755navDwDAOT4A0GH9+/f3elxZWSljjOLi4hQcHOz1Z8eOHTpy5IgkKSIiQsXFxUpLS9OyZcs0atQoDRgwQKtWrVJDQ0Or66uqqlJ8fHyz8ZbGfLV582bdfPPNGjhwoDZu3KhPP/1Un3/+ue68807V19d3eLlnbpuqqio1Njbq6aefbrZtrr32WknybJ+//e1v+te//qUdO3bommuuUUxMjCZNmqSdO3d6lpeTk6MVK1Zo6tSp2r59uz777DN9/vnnSk1N1YkTJ5rliY6O9npst9vPOn7maz/bdq+qqmp7g5whJiam2VhISIhX9qqqKq+y1aSlMQBA2zjHBwA66MyT1mNjY2Wz2fTxxx8rJCSk2fzfj40ePVqvvPKKjDHau3evCgoKtHr1ajkcDi1durTF9cXExKiioqLZeEtjoaGhOnnyZLPxI0eOeH2DsHHjRiUkJOjVV1/1ej0tPbc9ztw2UVFR6t27t2bMmKF77723xeckJCRIkoKCgpSTk6OcnBwdPXpU77//vpYtW6arrrpK5eXlcjqd2rhxo2bOnKlHH3202euLjIw8p+wtOdt2b6nEdIaYmBhVVlb6lAUA0DaKDwB0kszMTD322GM6dOiQz4cj2Ww2paamau3atSooKNCuXbtanTthwgStWbNGe/bs8TrcrbCwsNncoUOHau/evV5j3333nb799luv4mOz2WS3272KSkVFxTld1a0lTqdTEyZM0O7duzVmzBjPNyttiYyMVFZWlg4dOqSFCxfqwIEDSklJkc1ma1Yu33rrLR06dEhJSUmdml2SPvjgA1VWVnq+bTl16pReffVVJSYmdtnlqtPT0/X22297ldXTp0/rtdde65L1AYDVUXwAoJOMGzdOc+bM0axZs7Rz506NHz9eYWFh+uGHH/TJJ59o9OjRmjt3rt58803l5uZq6tSpuuCCC2SM0ebNm3X06FFlZGS0uvyFCxdq/fr1mjx5sh555BHPVd1KSkqazZ0xY4amT5+uefPm6cYbb1RZWZnWrFmjfv36ec3LzMzU5s2bNW/ePGVlZam8vFwPP/yw+vfvr3379nXq9nnyySd1+eWX64orrtDcuXM1dOhQ1dXVqbS0VNu3b9eHH34oSZoyZYouvPBCXXzxxerXr5/Kysr073//W0OGDFFycrInd0FBgUaMGKExY8boiy++0D//+c8uKyGxsbGaOHGiVqxY4bmqW0lJiU+XtO6oBx54QNu3b9ekSZP0wAMPyOFwKC8vz3MFwV69OFodANqD4gMAnWjdunX685//rHXr1ik3N1enT5/WgAEDNG7cOF1yySWSpOTkZEVGRmrNmjU6fPiw7Ha7hg8froKCAt1+++2tLjs+Pl7FxcW67777NHfuXDmdTk2bNk3PPPOMrr/+eq+52dnZOnz4sPLy8vTCCy/owgsv1HPPPaeHHnrIa96sWbP0448/Ki8vT+vXr9cFF1ygpUuX6uDBg83mnquUlBTt2rVLDz/8sJYvX64ff/xRkZGRSk5O9pznI7m/2Xr99deVn5+v2tpaxcfHKyMjQytWrFBwcLAkd4kKDg7W3//+dx07dkwXXXSRNm/erOXLl3dq5ibXXXedRo0apeXLl+t///ufEhMTtWnTJt1yyy1dsj5JSk1N1XvvvafFixdr5syZioqK0owZM5Senq4lS5YoIiKiy9YNAFZkM8YYf4cAACBQ2Ww23XvvvXrmmWf8HUWS9Je//EUHDhzQd9995+8oANCj8I0PAAABKicnR2PHjtXgwYNVXV2tTZs26b333tPzzz/v72gA0ONQfAAACFCnTp3SypUrVVFRIZvNppSUFL300kuaPn26v6MBQI/DoW4AAAAALI9LwgAAAACwPIoPAAAAAMuj+AAAAACwPJ8vblBfXy+Xy9WVWQAAAACgXex2u0JDQ9uc51Pxqa+vlyM6QTpRcc7BAAAAAKCzxMfHa//+/W2WH5+Kj8vlcpee7HLJHt4pAf3mDn8HwJlqxN3H0YUK/B0A6BkiVOPvCDjTHf4OACurKbDG/letSxpcWCGXy9U5xcfDHt7zi08ffwfAmXr4OwqBzu7vAEBPwadxwGGfBV0o/A/4+5GLGwAAAACwPIoPAAAAAMuj+AAAAACwPIoPAAAAAMuj+AAAAACwPIoPAAAAAMuj+AAAAACwPIoPAAAAAMuj+AAAAACwPIoPAAAAAMuj+AAAAACwPIoPAAAAAMuj+AAAAACwPIoPAAAAAMuj+AAAAACwPIoPAAAAAMuj+AAAAACwPIoPAAAAAMuj+AAAAACwPIoPAAAAAMuj+AAAAACwvCB/BwACkTHS9welqhopJkJKHCTZbP5ORS70fMZI39dKVSelmBApMZz3CtBjGCMd/F6qqZIiYqRBiYHxD5hc8BHFB/gdY6T8LdIThdLPtZKrQbIHS1HhUk62NHuafz6zyIWezhgpv0R64ivp55OS65Rk7y1FhUg5o6XZI3ivAAHLGGlLvlT4hFT7s9TgkoLtUniUlJ0jTZvtv19C5EI72Iwxpq1JtbW1ioiIkO6okezh3ZGr68zxdwCcySgw/vEbI81cKW0rluqON/95X6d0fbr04urLine truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1281,7 +1281,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1352,7 +1352,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1426,7 +1426,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1436,7 +1436,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1446,7 +1446,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1456,7 +1456,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1537,7 +1537,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.8.3"
   }
  },
  "nbformat": 4,