# Syllabus – Math 6316, Numerical Linear Algebra, Spring 2014¶

## Instructor:¶

Daniel R. Reynolds

## Class and Office Hours:¶

Lecture: 224 Clements Hall, M/W/F, 9:00-9:50 am.

Office Hours: 139 Clements Hall, M/F 3-5, W 1-3, or by appointment (arrange by email).

## Textbook:¶

D.S. Watkins, Fundamentals of Matrix Computations, Wiley, 3rd edition, 2010. (ISBN: 0470528338)

## Course Description:¶

MATH 6316 – Numerical Linear Algebra [3 credits]

The efficient solution of dense and sparse linear systems, least squares problems and eigenvalue problems. Elementary and orthogonal matrix transformations provide a unified treatment. In addition to algorithm development, the course will emphasize the theory underlying the methods.

Prerequisites: MATH 5315 or CSE 7365 or consent of instructor.

## Educational Outcomes:¶

• Students will be able to master theoretical properties related to important matrix decompositions, including QR, LU, Eigen-decomposition, and SVD.
• For each matrix decomposition, students will be able to understand the its importance, what are its applications, and what are the main ideas behind the standard numerical algorithms used in its computation.
• Students will be able to correctly code certain standard numerical algorithms for solving linear equations, least square problems, and eigenvalue problems.

## Computing:¶

Computing assignments in this class will be performed in Matlab, unless otherwise approved by the instructor. Because SMU has a site license for Matlab, it is available on most public computers across campus. This includes all Lyle computer labs, all Math department graduate student workstations, and the Math department servers.

As this class focuses on linear algebra, students may install the open-source Matlab clone, Octave, to do their computing work at home, if they do not wish to purchase a student version of Matlab.

Alternately, students may run Matlab remotely from either the Math or Lyle servers (if they have accounts) – students who do not yet know how to do this and own Windows computers should follow the instructions here to set up the appropriate software on their computer to allow them to emulate and/or login to Unix/Linux servers. Students running OS X can follow these instructions to log into Unix/Linux servers from their Mac.

Reading the sections of the textbook corresponding to the current lecture topic is required, and will be necessary for completing each homework assignment. It is expected that you have read this material in advance of each lecture.

## Homework:¶

Homework will be assigned on the course Homework page. These will be due periodically throughout the semester, and will be comprised of both theoretical and computational (Matlab) work.

## Exams:¶

We will have 2 in-class exams, the dates of which are posted on the course web page. The exam questions will be based off of the reading and homework. These exams will be non-cumulative, and will be open-book/open-notes, but no calculators.

Our third exam will occur during the regularly-scheduled final exam period. This will also be non-cumulative, is also open-book/open-notes, and calculators are not allowed. Although it will occur during the final exam time slot, it will only last 90 minutes.

The specific sections covered on each exam will be provided on the Exams page.

25% Homework

25% Each exam

## Honor Code:¶

The SMU Honor Code applies to all homework and exams in this course. Work submitted for evaluation must represent your own individual effort. Any giving or receiving of aid without my express consent on academic work submitted for evaluation shall constitute a breach of the SMU Honor Code.

Academic dishonesty is considered a serious offense, and is doubly inexcusable among graduate students. I take honor code violations very seriously, and will report all violations to the SMU Honor Council. The minimum penalty for a violation is a “0” on the assignment, and the maximum penalty is immediate failure of the course. These penalties are in addition to those imposed by the SMU Honor Council.

The line between helping each other learn, and copying from one another is not always easy to discern. While I strongly encourage you to learn with/from one another, you should never turn in anything that you do not understand or could not reproduce on your own. If I feel that you may have gone too far, I reserve the right to ask you to repeat your work in my office to see whether you did it yourself, or just copied answers from a friend.