Advanced Numerical Linear Algebra
''Advanced topics in numerical linear algebra including pseudo-spectra, rounding error analysis and perturbation theory, numerical methods for problems with special structure, and numerical methods for large scale problems.
Basic iterative methods for linear systems and linear eigenvalue problems; deflation techniques; general projection methods; Krylov subspace methods; pre-conditioning; multigrain methods; domain decomposition methods; perturbation theory and error analysis; non-standard eigenvalue problems.
Students should be comfortable with concepts from linear algebra (Math 590 and (or) Math 591) and numerical analysis (Math 781 and 782), e.g. Gaussian elimination; LU, Cholesky and QR factorization; QR algorithm. Programming assignments will be an essential part of the course. If you have any questions about the course prerequisites, please contact the instructor.
(Miedlar 2020 )