Lectures related to Spline Interpolation and Approximation

Explores spatial transformations, polynomial splines, B-spline properties, interpolation, and differential operators in image processing.

Provides an overview of polynomial interpolation techniques in numerical analysis, focusing on Lagrange interpolation and error estimation methods.

Explores linear regression, least squares, residuals, and confidence intervals in regression models.

Covers regression methods focusing on spline smoothing and penalised fitting to balance data fidelity and smoothness.

Covers modeling response surfaces in Matlab, including building the model, defining the domain, computing values, and analyzing residuals.

Covers polynomial interpolation, error analysis, stability, and piecewise linear interpolation using equally distributed nodes.