Matrix Computations

Students will learn techniques for the solution of dense and sparce systems of linear equations, least squares problems, eigenvalue problems, and singular value problems. They will also learn to apply principles generally applicable to the engineering of numerical software: matrix factorizations, iterative methods, perturbation theory and condition numbers, effects of roundoff error on algorithms, performance analysis, choice of the best (fastest and/or most accurate) algorithn based on mathematical structure of the problem. PREREQ: course on Linear Algebra at the undergraduate level. (lec 3) cr 3. Lecture (3.00)