Mathematics 726
Numerical Analysis I
MWF, 11:15 a.m. - 12:05 p.m., LC 316
- Instructor:
- Ralph Howard
- Office: LC 304
- Phone: 777-2913
- E-mail: howard@math.sc.edu
- Office Hours:
Tuesdays and Thursdays 1:00-2:00 p.m. Wednesday 2:00p.m.-3:00p.m
- Examples of MATLAB programs:
-
- Defining special vector and matrices
shows how to define the zero vector and matrix along with some other
related facts.
- Getting information about a matrix
gives examples of how to recover the size of a matrix.
- inner.m Computes the inner product of two
vectors from the definition.
- matvect.m Computes the product of a
matrix times a vector from the definition.
- mat.m by Keith Morris. Computes a matrix
product from the definition.
- rowmat.m by Li Chong. Computes the
matrix product AB as a linear combiations of the rows of
B. This version also tests to see if the matrices are of the
correct dimensions and is generally written in a very nice manner.
- inmat.m by Martha Allen. This computes
the matrix product as the inner product of rows and columns. It tests
to see if the matrices are of the correct dimensions.
- Text:
- Matrix Computations 3 rd Edition
by G. H. Golub and C. F. Van Loan
-
Computer Accounts:
- The course will involve
computer programming (mostly with the two packages MatLab and Maple).
Those of you who are graduate students in the mathematics department
should already have accounts on our machines. If you do not have a
such an account see me and we will get one set up.
- Grading:
- There will be regular homework assignment with will include some
longer terms computer projects and some oral presentations in class.
Sometimes homework will be in the form of things to learn by the next
class and which will be "collected" in the form of a short
in class quiz. Lastly there will be a final at the end of the term.
The grade will be based on the total performance on the homework and
final.
- Course Content:
- Mathematics 726 and 727 are a year long sequence in
numerical analysis. The first term will center on numerical linear
algebra, which is fundamental to much of the rest of numerical
analysis. Concretely this is the material in chapters 1-5, 7 and 8 of
Golub and Van Loan.
- Homework:
- For most of the assigned problems you are encouraged to work
together. Also feel free to come ask me or other faculty members
questions. Occasionally there will be problems that should
be done on your own, but unless I say otherwise collaboration (short
of copying) is the rule.
- Date of Final Exam:
-
Wednesday, April 29 - 2:00 p.m
- MATHLAB Resources:
- Most of the following list was down loaded form a
tutorial made by Nam Sun Wang
of the University of Maryland.
-
Tutorial at the University of Alberta.
-
Tutorial by Mark Austin of University of Maryland.
-
Tutorial at Chinese University of Hong Kong.
-
Tutorial at Bucknell University.
-
Tutorial by Lai Loong Fong of National University of Singapore.
-
Tutorial by Steve McKelvey of Saint Olaf College.
- Tutorial from MIT's Athena (37 pages).
- Tutorial from Gilliam.
- Tutorial from Ellinger/Barry University of Illinois at Urbana-Champaign
(33 pages).
- Tutorials from Cargegie-Mellon University and the University of Michigan
(55 pages, especially aimed at control).
- Tutorial from Prof. Tilbury at the University of Michigan (old version of the above control stuff, 36 pages).
- Tutorial from Michigan State
(The last section #16 on Workshop Handouts greatly expands to a total of 67 pages).
- Brief Tutorial from the University of Texas (10 pages).
- Brief Tutorials by A. E. Traver at the University of Texas (21 pages).
- Brief Tutorials by David Hart at the Indiana University (11 pages).
- Tutorial from the University of Wales Swansea (similar to the one from Indiana University).
- Tutorial by Prof. Sam Davis at Rice University (106 pages).
- Another Tutorial from the University of Florida (27 pages).
- Tutorial by R. Smith at the Unveristy of Florida.
- Brief Introduction by Prof. Lee Potter at Ohio State University.
- Tutorial by Prof. Sean Willett at Penn State University (11 pages).
- Introduction to MATLAB by Panduka Wijetunga at the University of Southern California.
- Brief Tutorial from the Mathematics Department at the University of Utah (6 pages).
- Tutorial by Lai Fong (18 lessons, ~80 pages).
- Quick Reference Guide from the University of Waterloo (10 pages).
- Tutorial from SUNY Buffalo.
- Tutorial from University of New Hampshire (28 pages).
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