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+     "source": [
+      "[Table of Contents](http://nbviewer.ipython.org/github/rlabbe/Kalman-and-Bayesian-Filters-in-Python/blob/master/table_of_contents.ipynb)"
+     ]
+    },
+    {
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+     "metadata": {},
+     "source": [
+      "$H_\\infty$ filter"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "#format the book\n",
+      "%matplotlib inline\n",
+      "from __future__ import division, print_function\n",
+      "import sys\n",
+      "sys.path.insert(0,'../code') # allow us to format the book\n",
+      "import book_format\n",
+      "book_format.load_style()"
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+        "<IPython.core.display.HTML at 0x7f16501445f8>"
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+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "I am still mulling over how to write this chapter. In the meantime, Dan Simon has an accessible introduction here:\n",
+      "\n",
+      "http://academic.csuohio.edu/simond/courses/eec641/hinfinity.pdf\n",
+      "\n",
+      "In one sentence the $H_\\infty$ (H infinity) filter is like a Kalman filter, but it is robust in the face of non-Gaussian, non-predictable inputs.\n",
+      "\n",
+      "\n",
+      "My filterpy library contains an H-Infinity filter. I've pasted some test code below which implements the filter designed by Simon in the article above. Hope it helps."
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "from __future__ import (absolute_import, division, print_function,\n",
+      "                        unicode_literals)\n",
+      "\n",
+      "from numpy import array\n",
+      "import matplotlib.pyplot as plt\n",
+      "\n",
+      "from filterpy.hinfinity import HInfinityFilter\n",
+      "\n",
+      "dt = 0.1\n",
+      "f = HInfinityFilter(2, 1, 0, gamma=.4)\n",
+      "\n",
+      "f.F = array([[1., dt],\n",
+      "             [0., 1.]])\n",
+      "\n",
+      "f.H = array([[0., 1.]])\n",
+      "f.x = array([[0., 0.]]).T\n",
+      "#f.G = array([[dt**2 / 2, dt]]).T\n",
+      "\n",
+      "f.P = 0.01\n",
+      "f.W = array([[0.0003, 0.005],\n",
+      "             [0.0050, 0.100]])/ 1000\n",
+      "\n",
+      "f.V = 0.01\n",
+      "f.Q = 0.01\n",
+      "\n",
+      "xs = []\n",
+      "vs = []\n",
+      "\n",
+      "for i in range(1,40):\n",
+      "    f.update (5)\n",
+      "    print(f.x.T)\n",
+      "    xs.append(f.x[0,0])\n",
+      "    vs.append(f.x[1,0])\n",
+      "    f.predict()\n",
+      "\n",
+      "plt.subplot(211)\n",
+      "plt.plot(xs)\n",
+      "plt.subplot(212)\n",
+      "plt.plot(vs)\n",
+      "plt.show()\n"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "[[ 0.250005  2.50005 ]]\n",
+        "[[ 0.66806083  3.34442646]]\n",
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18JVPbuRLn1hPctKCaQIRWUAWRGZ7ufoUT/2omt6BYVYWpPN//+tHKVvu7IGC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\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x7f164f16d518>"
+       ]
+      }
+     ],
+     "prompt_number": 5
+    }
+   ],
+   "metadata": {}
+  }
+ ]
+}
\ No newline at end of file