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https://github.com/AtsushiSakai/PythonRobotics.git
synced 2026-04-22 03:00:41 -04:00
#fix 281 and doc clean up
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@@ -360,9 +360,7 @@
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"\n",
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"$$\\mu_\\mathtt{new} = \\frac{\\mu_1 \\sigma_2^2 + \\mu_2 \\sigma_1^2}{\\sigma_1^2+\\sigma_2^2}$$\n",
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"New variance is\n",
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"$$\n",
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"\\sigma_\\mathtt{new} = \\frac{\\sigma_1^2\\sigma_2^2}{\\sigma_1^2+\\sigma_2^2}\n",
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"$$"
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"$$\\sigma_\\mathtt{new} = \\frac{\\sigma_1^2\\sigma_2^2}{\\sigma_1^2+\\sigma_2^2}$$"
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]
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},
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{
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@@ -755,6 +753,15 @@
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.6"
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},
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"pycharm": {
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"stem_cell": {
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"cell_type": "raw",
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"source": [],
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"metadata": {
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"collapsed": false
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}
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}
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}
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},
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"nbformat": 4,
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@@ -35,7 +35,7 @@
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"\n",
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"If $x_{t}$ is complete, then:\n",
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"\n",
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"$$p(z_{t} | x-_{0:t},z_{1:t-1},u_{1:t})=p(z_{t} | x_{t})$$\n",
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"$$p(z_{t} | x_{0:t},z_{1:t-1},u_{1:t})=p(z_{t} | x_{t})$$\n",
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"\n",
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"$x_{t}$ is **complete** means that the past states, controls or measurements carry no additional information to predict future.\n",
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"\n",
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@@ -365,8 +365,17 @@
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.6"
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},
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"pycharm": {
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"stem_cell": {
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"cell_type": "raw",
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"source": [],
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"metadata": {
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"collapsed": false
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}
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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}
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