MA 537, Numerical Analysis I

Review of basic linear algebra from a constructive and geometric point of view. Factorizations of Gauss, Cholesky and Gram-Schmidt; determinants; linear least squares problems; rounding error analysis; stable methods for updating matrix factorizations and for linear programming; introduction to Hermitian eigenvalue problems and the singular value decomposition via the QR algorithm and the Lanczos process; method of conjugate gradients. (Same as CS 522.)
Prerequisite: MA 322.
Possible Instructors: Kang, Kim, Li, Ye.
Status of Course: Course functioning.