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I'm trying to understand well the kalman filter, as a result i'm having this question : Why do we represent noise with a Gaussian ? what does this really mean intuitively ?

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migrated from cs.stackexchange.com Apr 28 '17 at 13:40

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  • $\begingroup$ This may be more ontopic on Signal Processing. Do you want us to migrate your question there? Either way, I think you can improve your question by including some of your own thoughts, and which resources you have consulted. (This does sound like a rather basic question, so I assume it's covered in the pertinent textbooks.) $\endgroup$ – Raphael Apr 27 '17 at 19:08
  • $\begingroup$ Yeah it is a basic question I think, I read the original paper of kalman 1960 where it's written that this is an assumption, but I can't figure out why I don't find it that intuitive. And yeah thanks for proposing to migrate the question i would like it if you do ! $\endgroup$ – Calips Apr 28 '17 at 12:56
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    $\begingroup$ General remark: original research articles are usually a poor learning resource. In particular, assumptions common to the field won't be discussed. Textbooks on the matter (often written decades later) will discuss such things, so I recommend you check one out. $\endgroup$ – Raphael Apr 28 '17 at 13:39
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    $\begingroup$ I might have some intuitions on Gaussian noise in general to share, but I'd like to know that you want Gaussian noise definition in Kalman filtering context only? $\endgroup$ – MimSaad Apr 28 '17 at 17:38
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    $\begingroup$ this answer helped me understand why. But more of a data based answer than intuition. $\endgroup$ – harshkn Apr 29 '17 at 2:46

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