Given:
then matching procedure assumes searching for the specific set of model parameters to minimize the goal function:
G({\bf p}) = \sum_{k=1}^N \, \Psi \left( y^*(x_k) - y_k \right) \rightarrow \textrm{min} \ \Longleftrightarrow \ {\bf p} = {\bf p}_{\rm bestfit} |
where is the discrepancy distance function.
The most popular choices are and .
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