Description: The aim of this
course is to introduce the essential ideas of numerical
linear algebra, to describe some of the important
algorithms in the subject, and to possibly offer a
glimpse of some of the current research problems. Matlab
will be the scientific programming language for this
course. Assignments may involve a fair amount of
scientific programming in matlab together with more
classical exercises
Prerequisite:  Ma 1abc, Ma
2ab, ACM 95(abc). Students should be comfortable with
linear algebra (undergraduate level). Some programming
experience or some willingless to learn. Prior
knowledge of matlab not required.
Syllabus:

 Introduction to numerical computation
 Direct methods for linear systems
 QR decompositions and Least Squares problems
 Eigenvalue and eigenvector computations
 Iterative methods for large linear systems
and eigenvalue problems
 Stability and conditioning
The course will also develop applications in
inverse problems, data fitting, optimization and other
areas.
Textbooks:
 Numerical Linear Algebra by LLoyd N. Trefethen and David
Bau, III, SIAM (required)
 Applied Numerical Linear Algebra by James W. Demmel, SIAM
(optional)
 Matrix Computations by Gene H. Golub and Charles F. Van Loan, The
Johns Hopkins University Press, 3rd edition (optional)
 Introduction to Linear Algebra
by Gilbert Strang, WellesleyCambridge Press, 3rd edition (optional)
Handouts: I will do my best to
post online all the handouts given in class. By the way,
Sheila Shull (217 Firestone) is a person you can contact
at any time (between 9:30am and 5pm) if you need
administrative information. Her phone number is
6263954560.
Teaching
Assistant and Office Hours:
Svitlana Vyetrenko, TBA, 322 Guggenheim
svitlana@acm.caltech.edu
Grading:
Homework assignments: 60%
Homework will generally be distributed on Wednesdays and
due in class the following Wednesday.
There will be about 5 assignments, and your
lowest score will be dropped in the final grade.
Late homeworks will NOT be accepted for grading
(medical emergencies excepted with proof).
Final exam: 40%. There will be a
takehome final exam.
