Moved chapter 7 as part of reorg

07_Kalman_Filter_Math.ipynb

@@ -1,7 +1,7 @@
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-  "signature": "sha256:f6eb3441648c1a743a0155aaa4a53c9703d22947e978a0eb7a6bce0eadc6a698"
+  "signature": "sha256:f8dcc12ca7ce84bf0c76ff9c37aab41847d1661cdde92d0fcb8b409ae6520cc6"
  },
  "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 0x7f44082d1128>"
+        "<IPython.core.display.HTML at 0x7f84da330438>"
        ]
       }
      ],
@@ -633,7 +633,7 @@
         "        IEEE Trans. Automomatic Control, AC-23 (3): 395-404 (June 1978)\n",
         "    \n",
         "    [2] Robert Grover Brown. \"Introduction to Random Signals and Applied\n",
-        "        Kalman Fitlering.\" Forth edition. John Wiley & Sons. p. 126-7. (2012)\n",
+        "        Kalman Filtering.\" Forth edition. John Wiley & Sons. p. 126-7. (2012)\n",
         "\n"
        ]
       }
@@ -739,7 +739,7 @@
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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f43e8fb7e48>"
+        "<matplotlib.figure.Figure at 0x7f84b64b7c50>"
        ]
       }
      ],
@@ -1294,9 +1294,9 @@
        "output_type": "pyout",
        "prompt_number": 13,
        "text": [
-        "array([[  1.56250000e-08,   7.81250000e-07,   2.08333333e-05],\n",
-        "       [  7.81250000e-07,   4.16666667e-05,   1.25000000e-03],\n",
-        "       [  2.08333333e-05,   1.25000000e-03,   5.00000000e-02]])"
+        "array([[ 0.00000002,  0.00000078,  0.00002083],\n",
+        "       [ 0.00000078,  0.00004167,  0.00125   ],\n",
+        "       [ 0.00002083,  0.00125   ,  0.05      ]])"
        ]
       }
      ],

07_Kalman_Filter_Math/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)