Numerical Interpolation & Differentiation

Interpolate and Differentiate numerical datasets by generating a function for equal interval using Newton Forward/Backward & Sterling Method

NumericalDifferentiation

This MATLAB program is designed to analyze datasets by generating a function based on the provided data. It then conducts differentiation on the generated function. The program utilizes Newton's Forward/Backward Difference and Stirling's method for this purpose, which requires that the interval of the independent variable remains consistent across the dataset.

Here's a summary of the steps the program takes:

Function Generation: The program evaluates the provided datasets to generate a function that approximates the relationship between the independent and dependent variables. It uses techniques like Newton's Forward/Backward Difference and Stirling's method.

Differentiation: The program performs differentiation up to a specified order on the generated function.

Evaluation: After differentiation, the program allows users to evaluate either the original function or its derivative at specified points of interest.

Note on Interval: The datasets must have equal intervals for the independent variable to ensure accurate results when using techniques like Newton's Forward/Backward Difference and Stirling's method.