Lectures related to Image Processing II: B-spline Properties and Gradient Operators

Covers the Newton method for finding zeros of functions using data interpolation.

Covers logical arrays, 3D surface plotting, parametric curves, interpolation, and fitting in Matlab.

Covers the optimization of error in polynomial interpolation, focusing on minimizing the error by strategically placing interpolation points.

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

Explores modeling and interpolation techniques in geomatics for accurate surface generation.

Covers the fundamentals of finite element analysis and the application of constitutive laws.

Explores polynomial interpolation theory, emphasizing error expression and piecewise definition.

Covers revisions on calculus, derivation rules, interpolation, and tangent vectors.