Spline Interpolation and Approximation

Related lectures (26)

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Explores cubic splines and least-squares approximation, focusing on interpolation methods and error analysis.

Explores splines, emphasizing the least-squares method for interpolating splines and demonstrating its application using MATLAB.

Explores B-splines, natural cubic splines, and smoothing splines in regression problems and their practical applications.

Explains spline interpolation and error analysis in approximating data points using piecewise linear and spline methods.

Covers the least squares method for approximating data and handling errors.

Explores challenges in polynomial approximation, stability issues, and error analysis in numerical differentiation.

Covers polynomial interpolation and least-squares approximations to minimize errors.

Covers piecewise linear and spline interpolation methods, stability, convergence, and data interpolation using splines.

Explores image interpolation, splines, wavelets, and geometric transformations in image processing.

Explores error analysis and limitations in interpolation on evenly distributed nodes.