Timeline for Is there a (family of) monotonically non-decreasing noise function(s)?
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| Mar 29, 2012 at 14:20 | comment | added | user744 | As an example, Perlin noise takes a seed state of 255 8 bit numbers, but from that it generates random noise in infinite distance in three dimensions; it's not really accurate to describe them as "guide points", mathematically they are more like another 256 parameters you don't want to keep providing. As you say it's essentially not integrable, but it is a pure function. The page you linked to is a bad explanation of Perlin noise (it's not really Perlin noise he explains). As for whether it's possible for some kind of noise function... well, that's the question, isn't it? | |
| Mar 29, 2012 at 13:38 | comment | added | teodron | Hmm, sorry, I thought that noise functions also use a random number generator procedure and that are also dependent on a discrete set of guide/key points to yield a shape (I saw Perlin Noise was mentioned.. that one works via pseudo-random number generators that are quite difficult to integrate, hence no analytic solution). Can one integrate a noise function analytically? I am wondering if one of these could be a candidate link | |
| Mar 29, 2012 at 12:55 | comment | added | user744 | "there's actually no mathematical formula for a random function" I want a noise function, not a random function. Noise functions are well-documented to exist. Piecewise definitions like this also tend to create either inefficiency (evaluating becomes O(pieces) which becomes a problem when you have long time scales), impure functions (evaluate in O(1) but need to keep the previous position), or over-constrain possible functions (e.g. all inflection points are at fixed intervals). | |
| Mar 29, 2012 at 12:36 | history | answered | teodron | CC BY-SA 3.0 |