Instructor: Ed
BuelerOffice: Chapman 301C.Phone: 474-7693eMail: elbueler@alaska.edu |
Class Times & Room: MWF 9:15--10:15 Bunnell 410CRN: 78256Text: Trefethen & Bau, Numerical Linear Algebra, SIAM Press 1997 |

Applications of these ideas include solving large linear systems, solving systems of ordinary differential equations, statistical methods, inverse methods in geophysics, and Markov processes. Numerical linear algebra is key for numerically solving partial differential equations, network problems, and optimization problems.

Examples in class will often use Matlab/Octave. (Or python+scipy=pylab for students who are already comfortable with python.) I will help students learn how to use one of these tools, all of which are well-suited to numerical linear algebra. Student competence with such a language, for scientific computing though not necessarily general computer programming, is a goal of the course.

- matrix/vector mechanics
- geometric view of linear algebra
- singular value decomposition

- QR factorization and least squares
- conditioning and stability
- operation count and problem size

- systems of equations and Gaussian elimination

- computing eigenvalues
- iterative methods

WorkHomework In class Midterm Exam Take home Final Exam |
Percent of Grade 55% 20% 25% |
Dates nearly weekly Friday, 30 October, in class Due in my box 5:00 p.m., Wed., Dec. 16. |

Based on your raw homework and exam scores, I guarantee grades according to the following schedule: 90 - 100 % =