AMATH 352: Applied Linear Algebra and Numerical Analysis
SLN 10056, MWF 10:50-11:50, Guggenheim Hall 204
(Prerequisites: MATH 126 or MATH 136: recommended: CSE 142)
Instructor:
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Jonathan Claridge
Guggenheim 407
tel: 685-9395
fax: 685-1440
onath@amath.washington.edu
office hours: Mon 3-4pm, Thurs 3:30-4:30pm
at the AS Lab
(Room B022 in the Communications Bldg)
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Announcements
Last lecture is Monday, August 18. Bring your favorite digital picture to class.
Final exam details:
- Will be posted on Monday, August 18 by 5:00pm
- Due Thursday, August 21 by 5:00pm
- Work independently, but feel free to use notes, the interwebs, etc.
Course Description
The first part of this course will focus on linear algebra, looking at
the geometry of linear transformations, and then at solving linear systems
of equations. In particular, we'll look at how to approximate the solution
of a system that can't be solved exactly.
In the second part of the course, we'll see how this notion of approximation
can be applied to continuous functions. Then we'll explore how approximation
techniques can be applied to numerical computations.
Textbook
There is no required textbook for this course. I'm posting lecture
notes on the Course Materials
page.
You'll need to use
MATLAB extensively, and it might be worth buying the student version,
which runs about $100 at the UW Bookstore. Otherwise, plan on spending a
lot of time at the AS Lab
(Room B022 of the Communications Building).
There are also some free resources that are worth checking out:
Syllabus
June 29, 2008: I just updated the syllabus below.
We'll start off looking at some fairly conventional matrix-vector topics:
- Geometry of linear transformations
- Linear systems of equations
- Solution techniques for linear systems
- Linear least squares problems
The last of these topics deals with finding approximate solutions
to systems for which there is no exact solution.
This will lead us to approximating continuous functions, using many of the
same ideas we looked at when dealing with linear systems of equations.
We'll look at two types of approximations:
- Polynomial approximation
- Trigonometric approximation
Finally, we'll look at a few applications of these approximations. The most
natural ones to look at are probably:
- Numerical integration (a.k.a. quadrature)
- Numerical differentiation
Course Materials
I'll post lecture notes as I go, along with any MATLAB code I'd like you to use.
To avoid clutter, I'm putting all of this on a
separate page.
Schedule and Homework
There will be 6 homework assignments, a midterm, and a final exam. I'll
post homework assignments at least a week before they're due.
The dates below are my best guess here at the beginning of the quarter.
If they change, I'll make a very loud announcement in class, in addition
to updating them here.
| Homework and Exams |
Date (due date for HW) |
Homework Assignments |
Homework Solutions |
| First day of classes |
Monday, June 23 |
| Homework #1 |
Wednesday, July 2 |
352hw1.zip |
|
| Independence Day |
Friday, July 4 |
No class |
| Homework #2 |
due Friday, July 11 |
352hw2.zip |
HW#2 solutions |
| Homework #3 |
due Friday, July 18 |
352hw3.pdf |
| Midterm |
Wednesday, July 23 |
| Homework #4 |
Friday, August 1 |
352hw4.pdf, gausselim2.m
hints/backbone code
|
| Homework #5 |
Friday, August 8 |
352hw5.pdf
Supplement Page |
HW#5 solutions |
| Homework #6 |
Friday, August 15 |
352hw6.pdf
Supplement Page
|
HW#6 solutions |
| Final Exam |
Thursday, August 21 |
FinalExam.pdf |
Grading
Here's the grading scheme:
- 50% = Homework assignments, weighted equally
- 25% = Midterm
- 25% = Final Exam