One-Dimensional Moving Least Squares (MLS) Matlab Implementation
A MATLAB computational program for one-dimensional Moving Least Squares (MLS) method, designed for advanced curve fitting applications with configurable smoothing parameters
ICP Algorithm (Classic Implementation) with Moving Least-Squares Enhancement for Curve and Surface Fitting
Development of a curve and surface fitting method based on the Moving Least-Squares (MLS) approach, which significantly improves upon traditional Least-Squares (LS) methods. This implementation yields fitted curves and surfaces with higher accuracy and superior smoothness characteristics. Detailed explanation of MLS algorithm principles, including weight function implementation and neighborhood point selection strategies for optimal surface reconstruction.
MATLAB Implementation of Meshless Local Petrov-Galerkin (MLPG) Method
MATLAB code implementation of the Meshless Local Petrov-Galerkin method with enhanced numerical computation techniques
One-Dimensional Moving Least Squares (MLS) MATLAB Implementation
MATLAB implementation for one-dimensional Moving Least Squares (MLS) computation with code optimization strategies