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Auto-tools/Projects/OrangeFactor/Statistics: Difference between revisions
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Auto-tools/Projects/OrangeFactor/Statistics (view source)
Revision as of 20:59, 2 November 2010
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A weight less than 1 is typically chosen. The lower the weight, the less smooth a single pass will be, so typically more passes are run for lower weights which allows information (data) to propagate from further away nodes. The average is still heavily weighted towards local nodes, but less dramatically so. | A weight less than 1 is typically chosen. The lower the weight, the less smooth a single pass will be, so typically more passes are run for lower weights which allows information (data) to propagate from further away nodes. The average is still heavily weighted towards local nodes, but less dramatically so. | ||
To illustrate how these filters behave, first apply them to a line that rises linearly from 3 to 13 but has -/+ 3 variation for odd/even numbers, respectively. Assuming that this is "noise" (it is high frequency), then smoothing should approximate a linear rise. | To illustrate how these filters behave, first apply them to a line that rises linearly from 3 to 13 but has -/+ 3 variation for odd/even numbers, respectively. Assuming that this is "noise" (it is high frequency), then smoothing should approximate a linear rise. A weight of 0.25 was used for the weighted smoothing and three and ten smoothing passes were ran. | ||
[[File:Saw-three.png]] | [[File:Saw-three.png]] | ||
[[File:Saw-ten.png]] | [[File:Saw-ten.png]] | ||
It can be seen that unweighted (w=1) smoothing converged rapidly even with three iterations. With ten smoothing passes, the results are mostly the same, though the weighted (w=0.25) smoothing has better results along the edges. The endpoints are hard to get accurate with this type of filter as you only have information coming from one direction. | |||
[[File:Random-three.png]] | [[File:Random-three.png]] | ||