Advanced Numerical Methods

Systems of nonlinear equations: Newton-Raphson iteration, quasi- Newton methods; optimization problems: steepest descents, conjugate gradient methods; linear and nonlinear approximation theory. Least squares, singular value decomposition, orthogonal polynomials, Chebyshev and Fourier approximation, Pade approximation; matrix eigenvalues: power method, Householder, QL and QR algorithms.

The text will be announced later.

The mark will be based on a combination of computer-based assignments, tests and a final exam.