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MATH 629 (04888), Winter 2010

Numerical Analysis: Linear Algebra

Catalog Description:

In-depth analysis of numerical aspects of problems and algorithms in linear algebra.

Desired Learning Outcomes:

Students will have a deep understanding of numerical methods for linear algebra. They will know the standard methods and be able to analyze and learn new methods on their own.

Prerequisites:

MATH 511 & (544 OR 546). 511 is to ensure you know about matrices, vector spaces, etc. 544 or 546 is to ensure you have some experience with computers, and how to make them do numerical calculations. If you would like to take this course, but do not formally meet the prerequisites, please contact me.

Instructor:

Martin J. Mohlenkamp, mohlenka@ohio.edu, (740)593-1259, 315B Morton Hall.
Office hours: Monday 3:10-4pm, Tuesday 3:10-4pm, Thursday 3:10-4pm, and Friday 3:10-4pm.

Web page:

http://www.ohiouniversityfaculty.com/mohlenka/20102/629.

Class hours/ location:

MTuThF 2:10-3pm in 313 Morton Hall.

Text:

Numerical Linear Algebra, by Lloyd N. Trefethen and David Bau III. Society for Industrial and Applied Mathematics, 1997; ISBN 978-0-898713-61-9. (Become a student member of SIAM and buy it through them at a discount.) (The first 5 lectures are available online.)

Homework:

From each section of the book, two or so homework problems will be assigned, to be turned in two classes after we finish that section. Most problems are paper-and-pencil problems, but some require (Matlab) programming. One problem each week will be designated a "Good Problem", which means it must

• be typeset in LaTeX and
• demonstrate writing skills according to the Good Problems program.

Tests:

There will be three mid-term tests, in class.

Final Exam:

The final exam is on Wednesday, March 17, at 12:20 pm in our regular classroom.

Presentation:

Toward the end of quarter, you will be assigned one section of the book to formally present to the class, as if it was a seminar talk.

Grade:

Your grade is based on homework at 40%, three tests at 10% each, a presentation at 10%, and the final exam at 20%. An average of 90% guarantees you at least an A-, 80% a B-, 70% a C-, and 60% a D-. Grades are not the point.

Attendance:

Attendance and participation is very important in this course, since the learning model is based on group in-class activities. I do not count attendance in your grade, since absences will penalize you through your loss of learning.

Academic Dishonesty:

On the homework you may use any help that you can find, but you must acknowledge in writing what help you received and from whom or where. The tests and final exam must be your own work, and without the aid of notes, etc. Dishonesty will result in a zero on that work, and possible failure in the class and a report to the university judiciaries.

Special Needs:

If you have specific physical, psychiatric, or learning disabilities and require accommodations, please let me know as soon as possible so that your learning needs may be appropriately met.

Learning Resources:

Your classmates are your best resource. Use them!

LaTeX, Python, and Matlab resources.

Wikipedia's Numerical Analysis pages and the (skeletal) Wikiversity course on Numerical Linear Algebra.

Schedule