The digital image of the car produces a 297 x 425 matrix. The matrix
can be represented as a sum of rank one matrices. Using the
Singular Value Decompostion (SVD) we can approximate the original
matrix. This can be thought of as an image compression. The car WAS
mine, many years ago. It was a 1997 camaro SS.

Course Material
Text:
Matrix Analysis for Scientists and Engineers
by Alan J. Laub
Publisher:
SIAM: Society for Industrial and Applied Mathematics (December 1, 2004)
ISBN-10: 0898715768
ISBN-13: 978-0898715767

Software:
Octave
is need (i.e. required) for this course. Octave is a high-level
language interface, primarily intended for numerical computations.
It provides a convenient command line interface for solving linear
and nonlinear problems numerically. Octave is very similar to MatLab,
but it is FREE. All of the laptops in Lippitt 205 have Octave installed.
More details will be provided in class.

Online Lecture Notes:
I will be providing detailed lecture notes for some topics. You will be able to
download notes as a pdf file within the Sakai course shell. I may also post computer codes
in Sakai that you can use for your assignments/projects.

Homework
Homework will be assigned for section of the textbook we cover.
A list of homework problems
will be provided in class and also posted on the web.
Do NOT email your homework to me!
Homework must have

your name
list of problems assigned
complete solution (answers only will be given no credit)
multiple pages stapled
Very little tolerance is given to messy homework. If I cannot read it
or follow the solution, then it is marked incorrect. I do not require
typed homework, but I strongly suggest you type the homework problems.
I will not accept ANY late or incomplete homework assignments.

Goals
The primary aim of MTH 418 is to gain an adequate understanding of
matrix theory and linear algebra so that we can use the concepts
in applications. We will study determinants, vector spaces, linear transformations,
singular value decompositions, least squares, linear equations, eigenvalues,
canonical forms, QR decmpositions, and linear differential equations. Some
applications will involve GPS, web searching, and image deblurring.

Exams and Grade Evaluation
2 Exams 100 pts each 200 pts
Homework 150 pts - 200 pts
3 Projects 150 pts
Total points: 500 pts -550 pts

Grade is determined by summing up your points and dividing by the total
number of points.
A ..92%-100%
A- ..90%-91%
B+ ..87%-89%
B ..82%-86%
B- ..80%-81%
C+ ..77%-79%
C ..72%-76%
C- ..70%-71%
D+ ..67%-69%
D ..60%-66%
F ..0%-59%
Remark: Incompletes can only be given if you are passing the course.
Remark: No across the board curves allowed.
Remark: No extra credit allowed.

Projects
There will be three projects. The goals of the projects
are to use the concepts to solve real life applications. You can work
in groups, no more than three students per group. You must use a
computer software system to solve these applications. Octave is
very easy to use and is free. You can also use Mathematica or Matlab.
You can NOT use a graphing calculator, Excel, or code written by
someone who is not in your group. Projects MUST be typed, with
proper grammar. Points will be taken off for grammar (and spelling)
mistakes. Do NOT hand in computer code. Projects will be posted
on the web. All projects must be submitted
through Sakai. Do NOT email the projects to me!
Projects must have a list of all the names of everyone in your group.
I will not accept ANY late or incomplete projects.

Students with Disabilities
Any student with a documented disability should contact your instructor early in the semester so that he or she may work out reasonable accommodations with you to support your success in this course. Students should also contact Disability Services for Students: Office of Student Life, 330 Memorial Union, 874-2098. They will determine with you what accommodations are necessary and appropriate. All information and documentation is confidential.

Sakai
Sakai is being used in part to teach this course.
That means you should become familiar with using Sakai.
You can access Sakai at the following web address:
https://sakai.uri.edu/portal/
Use your e-campus id and your URI Webmail password.