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I read many sources about kalman filter, yet no about the other approach to filtering, where canonical parametrization instead of moments parametrization is used. So I would like to learn on examples how to use this filter with information matrix and information vector (not mean and covariance from KF). Can anyone help me with this, give some examples, webpages, or parts of implementation code to be a basis to learn? Really appreciate!

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Information filters are an application of a learning algorithm. One example of an information filter would be a recommendation system. On the other hand, a kalman filter is restricted to linear tracking. Its not learning per se.

If you are looking for machine learning/AI based approaches to SLAM, then you should probably look at Particle Filters.

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    $\begingroup$ This answer seems to be inaccurate or incomplete. An "information" filter is very similar to a Kalman filter in it's purpose, application and structure. The definition of the informtion filter differs from Kalman filter in a way that makes realization / computation less intensive. See archive.org/details/… for example. $\endgroup$ – user2718 Apr 5 '13 at 11:05
  • $\begingroup$ I think I got confused between Information Filtering Systems(like spam filter) and Information Filters(which I don't know about). $\endgroup$ – Naresh Apr 5 '13 at 11:26
  • $\begingroup$ @Naresh - You can revise your answer and get some positive feedback as a result. Nothing on this site is carved in stone. $\endgroup$ – user2718 Apr 5 '13 at 11:45
  • $\begingroup$ @Josh130 - Unfortunately I haven't implemented this kind of filter. Up to the present, all my filters have been of the non adaptive nature. I write some algorithms in C but mostly use existing algorithms from out DSP partner. $\endgroup$ – user2718 Apr 8 '13 at 2:19

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