Difference between revisions of "Weighted Least Squares (WLS)"

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[[File:image_1avhdsfej1b9cao01029m1e13o69.png|600px|thumb|upright=2|alt=1D MLS example|<caption>Example of 1D MLS approximation </caption>]]
 
[[File:image_1avhdsfej1b9cao01029m1e13o69.png|600px|thumb|upright=2|alt=1D MLS example|<caption>Example of 1D MLS approximation </caption>]]
 
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In general, approximation function can be written as
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\[\hat u({\bf{p}}) = \sum\limits_i^m {{\alpha _i}{b_i}({\bf{p}})}  = {{\bf{b}}^{\rm{T}}}{\bf{\alpha }}\]

Revision as of 17:20, 20 October 2016

One of the most important building blocks of the meshless methods is the Moving Least Squares approximation, which is implemented in the EngineMLS class.

1D MLS example
Figure 1: Example of 1D MLS approximation

In general, approximation function can be written as \[\hat u({\bf{p}}) = \sum\limits_i^m {{\alpha _i}{b_i}({\bf{p}})} = {{\bf{b}}^{\rm{T}}}{\bf{\alpha }}\]