Surface Fitting Different Algorithms
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I am recently working with the Surface Fitting. I came across three methods to do it, which are Regression, polynomial, interpolation and smoothing. I want to know about the algorithm used in each method. I dont understand the concept of Least Square Method. Is this is used in all surface fitting methods? Is there any documentation stating the algorithm used by each methods. How all the different surface fitting works and what is the maths behind it?
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Image Analyst
on 24 May 2019
Give an example of the data you want to fit a surface to, like a .mat file, or a screenshot, or both. Do you want the result to be a 2-D matrix with z values for every grid point? Do you want the fitted surface to match the existing training points (like a regression rather than a spline interpolation)?
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