daviddoji/Kalman-and-Bayesian-Filters-in-Python
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Roger Labbe 2014-06-01 16:45:12 -07:00
parent 74882a9e56
commit 366eb092e8
3 changed files with 55 additions and 38 deletions
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23
Kalman_Filter_Math.ipynb
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"This chapter is optional, especially the first time you go through this material. If you are a hobbiest you will be able to get quite far by just skipping this chapter and going on to learn the examples. However, to have any hope of reading the original Kalman filter or optimal estimation literature you will have to acquire some of the more formal mathematics. I will not endevour to teach linear algebra, statistics, or calculus here as each topic deserves a book on its own. \n",
"This chapter is optional, especially the first time you go through this material. If you are a hobbiest you will be able to get quite far by just skipping this chapter and going on to learn the examples. However, to have any hope of reading the literature or to design more sophsticated kilters you will have to acquire some of the more formal mathematics. I will not endevour to teach linear algebra, statistics, or calculus here as each topic deserves a book on its own. \n",
"\n",
"blah blah blah"
"blah blah blah\n",
"\n",
"**authors note: need to start with continuous equations with $\\phi$, etc. Then discuss linearization into discrete case.**"
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"\n",
"$\\mathbf{FPF}^T$ is the way we put $\\mathbf{P}$ into the process space using linear algebra so that we can add in the process noise $\\mathbf{Q}$ to it."
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66
Multidimensional_Kalman_Filters.ipynb
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4
g-h_filter.ipynb
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