Numerical Linear Algebra

3 credits · Graduate

The topics covered in this course include: matrix and vector norms, condition number, singular value decomposition, LU decomposition, QR decomposition, Cholesky decomposition, error analysis and complexity of matrix algorithms, Toeplitz matrix algorithms, orthogonalization and least squares methods, the symmetric and unsymmertric eigenvalue problems, and iterative methods. The student is expected to code most of the algorithms on the computer. PREREQUISITES: Ability to programme in C or Fortran.