daviddoji/Kalman-and-Bayesian-Filters-in-Python
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ipa-lth 2018-01-26 13:26:11 +01:00
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04-One-Dimensional-Kalman-Filters.ipynb
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@ -1788,7 +1788,7 @@
"\n",
"$$\\mu = \\left( \\frac{\\bar\\sigma^2}{\\bar\\sigma^2 + \\sigma_z^2}\\right) \\mu_z + \\left(\\frac{\\sigma_z^2}{\\bar\\sigma^2 + \\sigma_z^2}\\right)\\bar\\mu$$\n",
"\n",
"In this form it is easy to see that we are scaling the meaurement and the prior by weights: \n",
"In this form it is easy to see that we are scaling the measurement and the prior by weights: \n",
"\n",
"$$\\mu = W_1 \\mu_z + W_2 \\bar\\mu$$\n",
"\n",