Cubic Spline Interpolation with MATLAB Implementation
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Resource Overview
This article presents a MATLAB program for cubic spline interpolation, featuring straightforward code structure and detailed algorithm explanations to facilitate understanding of spline interpolation techniques.
Detailed Documentation
This article introduces a MATLAB implementation of cubic spline interpolation. Cubic spline interpolation is a widely-used numerical analysis method for curve fitting and function approximation. Compared to other interpolation techniques, it ensures second-order derivative continuity, delivering superior smoothness and accuracy in curve fitting applications. Our implementation includes both the core algorithm and comprehensive explanations of key computational steps, such as solving the tridiagonal system for spline coefficients using MATLAB's built-in matrix operations. The program demonstrates practical applications through multiple examples, showcasing how to handle boundary conditions (natural/clamped) and implement piecewise cubic polynomial calculations. These examples help users understand the method's theoretical foundations while providing ready-to-use code for real-world data interpolation tasks.
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