Surface Fitting Different Algorithms
1 回表示 (過去 30 日間)
古いコメントを表示
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?
6 件のコメント
Image Analyst
2019 年 5 月 24 日
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)?
回答 (0 件)
参考
カテゴリ
Help Center および File Exchange で Get Started with Curve Fitting Toolbox についてさらに検索
製品
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!