Fix all Notebook validation failed errors.

03-Gaussians.ipynb

@@ -208,9 +208,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1596,9 +1594,7 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2163,7 +2159,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {
@@ -2276,5 +2272,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

04-One-Dimensional-Kalman-Filters.ipynb

@@ -322,9 +322,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -529,9 +527,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -687,9 +683,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -770,9 +764,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1442,9 +1434,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2172,7 +2162,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {
@@ -4542,5 +4532,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

05-Multivariate-Gaussians.ipynb

@@ -1880,7 +1880,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {
@@ -2154,5 +2154,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

06-Multivariate-Kalman-Filters.ipynb

@@ -800,9 +800,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1390,9 +1388,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1440,9 +1436,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1803,9 +1797,7 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2351,9 +2343,7 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2405,9 +2395,7 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2661,9 +2649,7 @@
   {
    "cell_type": "code",
    "execution_count": 52,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -3132,7 +3118,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {
@@ -3516,5 +3502,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

07-Kalman-Filter-Math.ipynb

@@ -1668,9 +1668,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

08-Designing-Kalman-Filters.ipynb

@@ -2696,9 +2696,7 @@
   {
    "cell_type": "code",
    "execution_count": 56,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2892,9 +2890,7 @@
   {
    "cell_type": "code",
    "execution_count": 59,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -3978,7 +3974,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   },
   "widgets": {
    "state": {},
@@ -3986,5 +3982,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

09-Nonlinear-Filtering.ipynb

@@ -704,9 +704,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

10-Unscented-Kalman-Filter.ipynb

@@ -76,9 +76,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -171,9 +169,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -216,9 +212,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -416,9 +410,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -466,9 +458,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -514,9 +504,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -564,9 +552,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -879,9 +865,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -936,9 +920,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def f_cv(x, dt):\n",
@@ -985,9 +967,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1056,9 +1036,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1103,9 +1081,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def f_radar(x, dt):\n",
@@ -1138,9 +1114,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def h_radar(x):\n",
@@ -1165,9 +1139,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from numpy.linalg import norm\n",
@@ -1327,9 +1299,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1427,9 +1397,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1500,9 +1468,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1580,9 +1546,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1656,9 +1620,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1834,9 +1796,7 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1879,9 +1839,7 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1931,9 +1889,7 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1971,9 +1927,7 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2197,9 +2151,7 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2246,9 +2198,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "source": [
     "### Predict Step\n",
     "\n",
@@ -2285,9 +2235,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "source": [
     "The update step converts the sigmas into measurement space via the function `h(x)`.\n",
     "\n",
@@ -2375,9 +2323,7 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2466,9 +2412,7 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2535,9 +2479,7 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -3098,9 +3040,7 @@
   {
    "cell_type": "code",
    "execution_count": 56,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -3185,9 +3125,7 @@
   {
    "cell_type": "code",
    "execution_count": 58,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -3225,9 +3163,7 @@
   {
    "cell_type": "code",
    "execution_count": 59,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -3310,9 +3246,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

11-Extended-Kalman-Filters.ipynb

@@ -1001,9 +1001,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "source": [
     "Now we need to write that as a Python function. For example we might write:"
    ]
@@ -1033,9 +1031,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "source": [
     "We also need to define a function that converts the system state into a measurement."
    ]
@@ -1074,9 +1070,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "source": [
     "### Implementation\n",
     "\n",
@@ -1279,9 +1273,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1366,9 +1358,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1405,9 +1395,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1444,9 +1432,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1594,9 +1580,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

12-Particle-Filters.ipynb

@@ -691,9 +691,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -877,9 +875,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1098,9 +1094,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1429,9 +1423,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1546,9 +1538,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

13-Smoothing.ipynb

@@ -610,9 +610,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

14-Adaptive-Filtering.ipynb

@@ -337,9 +337,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -548,9 +546,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -647,9 +643,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -697,9 +691,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -969,9 +961,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1208,9 +1198,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1294,9 +1282,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1888,9 +1874,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2041,9 +2025,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

Appendix-A-Installation.ipynb

@@ -511,9 +511,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.5"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

Appendix-B-Symbols-and-Notations.ipynb

@@ -110,9 +110,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.5"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

Appendix-D-HInfinity-Filters.ipynb

@@ -152,9 +152,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

Appendix-E-Ensemble-Kalman-Filters.ipynb

@@ -536,9 +536,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

Appendix-G-Designing-Nonlinear-Kalman-Filters.ipynb

@@ -780,9 +780,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

Appendix-H-Least-Squares-Filters.ipynb

@@ -109,9 +109,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

Appendix-I-Analytic-Evaluation-of-Performance.ipynb

@@ -272,7 +272,10 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": []
@@ -281,7 +284,10 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": []
@@ -290,7 +296,10 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
    },
    "outputs": [],
    "source": []
@@ -312,9 +321,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }