Numerical Linear Algebra

Math 625 / CSI 740

Spring 2007


This is the web page http://math.gmu.edu/~wanner/courses/m625s07/index.html
It will be updated regularly and always contain the latest information on the course.

General Information:

Instructor: Thomas Wanner
Office: Room 226E, ST1
E-mail: wanner@math.gmu.edu
Web Page: http://math.gmu.edu/~wanner/
Phone: (703) 993-1472
Fax: (703) 993-1491
Office hours: MW 3:00-4:00pm, and by appointment

Lectures: M 7:20-10:00pm, Room 242, Science and Technology I
Prerequisites: Sufficient recall of undergraduate linear algebra and computer literacy including familiarity with Matlab.
Textbook: Numerical Linear Algebra by L.N. Trefethen and D. Bau (SIAM, 1997).


Important Links:


Syllabus:

This course covers theory and development of numerical algorithms for the solution of a variety of matrix problems. These include linear systems, least squares problems, eigenvalue problems, and the singular value decomposition. Both direct and iterative methods are covered, as well as analysis of sensitivity to rounding errors. A more detailed syllabus can be found here. It will be updated weekly.


Homework Assignments:

Homework problems will be assigned at the end of each class and posted on the homework page. These problems should not be handed in, but I advise everyone strongly to study them and write out the solutions properly. You are encouraged to discuss these problems amongst yourselves and make use of the office hours. I will go through many of the homework problems in the following class and you will not benefit from this if you have not made a serious attempt at solving them.


Matlab:

The software package Matlab will be used throughout the course. Matlab is a computing environment with programming capability, good graphics, and powerful library functions. It is available on campus on the Mason cluster and several Unix computer labs. Alternatively, a PC or Macintosh version can be purchased at the bookstore. Many Matlab tutorials are available: Also, the manual which comes with the PC version is very complete. Further information on Matlab can be found here.


Grading Policy:

Your final grade in the course will be determined from your performance in a midterm exam, a comprehensive final exam, and two numerical projects that will be given during the semester (dates to be announced). Weights for these items will be distributed approximately according to the following schedule:

Numerical Project 1 Numerical Project 2 Midterm Exam Final Exam
20% 20% 20% 40%


Thomas Wanner, January 12, 2007.