Course information for MATH 611:
Numerical linear algebra

Instructor
Prof. Toby Driscoll
505 Ewing Hall
831-3383 or driscoll(AT)math.udel.edu
Office hours: Tue 3:30-5:00, Wed 3:30-5:00, or by appointment
Meetings
MWF 2:30-3:20, in Ewing 205.
Textbook
L. N. Trefethen and D. Bau, Numerical Linear Algebra, SIAM.

We will not cover the text completely.

Additional reading: Matrix Computations by Golub and Van Loan (definitive reference), Elementary Numerical Analysis by Atkinson and Han (introductory reference)
Academic integrity
You are expected and encouraged to discuss problems with others. However, the work you turn in must be completely your own. For example, fixing an error in one line of a classmate's code is no big deal. Emailing your entire solution to someone is a big deal and is a violation of the integrity policy. So is working side-by-side and turning in the same code with some variable names changed.

Sharing or copying will result in grade penalties for all involved parties.

Homework
Homework will be collected on Fridays (not every week) at the start of class. After that time it is late with a penalty. After 5PM Friday, it will not be accepted without a valid excuse.
MATLAB
Using the software package MATLAB is a major required part of the course. I have written a basic guide that should be enough to get you through the class. If you want a more complete reference, I recommend Getting Started with MATLAB by R. Pratap. You can use MATLAB in certain campus labs, run it on the UNIX mainframes, or purchase a student version for about $100 from mathworks.com.

Homework problems using MATLAB will be required to be formatted usnig the "publishing" feature. Details will be given in class.

Labs
Some class meetings will be devoted to laboratory-style exercises using MATLAB.
Exams
There will be two midterm exams on nonoverlapping units of the course, plus a final.
Grading
Homework
40%
Labs 10%
Midterm exams
15% each
Final exam
20%
Synopsis
Sections Topic
1-5 I: Linear algebra fundamentals
6-11 II: QR factorization and least squares
12-15 III: Conditioning and stability
Oct. 24 Midterm 1
18-19 III: Conditioning and stability
20, 21, 23 IV: Square linear systems
24-29 V: Eigenvalues
Nov. 24 Midterm 2
32-36, 38 VI: Iterative methods for linear systems
-- Rootfinding and optimization
TBA Final exam