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Author Topic: Self similarity/ fractals from seemingly random distributions?  (Read 2958 times)
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coolphreak
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« on: June 18, 2007, 05:05:38 AM »

For anyone here who is familiar with fractals and self similarity:

Is it possible to find local self similar patterns from a random arrangement of objects which can apply to the global arrangement of these objects?

For example, we have people walking in a city. The positions are somewhat random. Let's just pretend that everyone is still. If I "zoom in" and take a random sampling of the positions/arrangement of people w/in the local space I zoomed in on, is it possible to extrapolate this data to the more "global" space of people in the whole city using self similarity methods? Hopefully this is not too confusing
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Nahee_Enterprises
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« Reply #1 on: June 19, 2007, 07:53:06 PM »

Is it possible to find local self similar patterns from a random arrangement of
objects which can apply to the global arrangement of these objects?

First of all...   Greetings, and welcome to this particular Forum!!   smiley

And based on the exact question above, I would say Yes it is possible, as long as all the variables about the "local space" are known.  For example, we could take a town in California, let's say El Dorado Hills.  Then we could choose a specific street, such as Terracina Drive.  If all the statistical information were made available (including current phase of the moon), then a pattern could be found that would be similar to the whole town, county, state.      wink

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