Lagrange Interpolation Implementation in MATLAB

Resource Overview

MATLAB code implementation for Lagrange interpolation with algorithm explanation and key function descriptions

Detailed Documentation

The implementation of Lagrange interpolation code in MATLAB can be accomplished through the following steps. First, define the data points for interpolation using arrays or matrices. Then, apply the Lagrange interpolation formula to calculate new data points by computing the weighted sum of basis polynomials. This process involves calculating weights for each data point using the formula L_i(x) = Π (x - x_j)/(x_i - x_j) for j≠i. The complete interpolation polynomial is constructed as P(x) = Σ y_i * L_i(x). Finally, visualize the results by plotting both original data points and the interpolated function curve using MATLAB's plot() function for further analysis. Through these steps, you can efficiently and accurately implement Lagrange interpolation, providing enhanced possibilities for your data analysis workflows. Key MATLAB functions involved include array manipulation, polynomial operations, and graphical plotting capabilities.