Final Project and Presentations
The final presentations will take place on the following three dates:
- Thursday Dec. 16th 5-7pm (there will be no class on Legislative
Day, Tuesday Dec. 14th)
- Tuesday Dec. 21st 5-7pm (in room
102!)
- Thursday Dec. 23rd 4-7pm (note the earlier start time!)
The final report (5-10 page writeup of
PDF, presentation, and any codes) is due Sunday Dec. 26th.
Notes about Homework Submissions
Logistics
- Submit a PDF of your writeup
and all of the source codes in
an archive (zip/tar/rar etc.),
and name files sensibly (e.g., not "A.m" or "script.m" but also not
"Solution of Problem 1 by Me.m"). Email them to me (donev@cims.nyu.edu) only (no need
to copy the grader).
- In general, one should be able to grade without looking at all
the codes. The reports should be
mostly self-contained, e.g., the figures should be included in
the writeup along with legends, explanations, calculations, etc. Do not include MATLAB codes in the writeup,
only the results. Put your name
on the writeup.
- Package the files so that the MATLAB codes can be run by us -- do
not put all the sources in one long text file, for example. Also, we do
not need your tex, lyx, Word, svn files etc., only a PDF of the final
product. Please make it easy for us
to find and examine the files quickly (there is 30 of you and
one grader!).
- If you are using Octave, do not
use double quotes for strings, use single quotes instead for
compatibility with MATLAB.
- For pen-and-pencil problems you can submit hand-written solutions
if you prefer.
- If you use any external source, even Wikipedia, make sure you
acknowledge it by referencing all help.
Present your information effectively
- Plot figures with thought and
care! For example, errors should be plotted on a logarithmic
scale, not linear, so you can see it going down instead of flat lines.
In problem 2 of Assignment 1, for example, you should have gotten the
hint to plot n*y_n or something related instead of , or in problem 3.3,
plotting \log(1+x)/x is better than \log(1+x). The plots should have
axes labels and be easy to understand
at a glance.
- A picture is worth a thousand
words! Some gave tables, or printouts of Matlab matrices, where
a plot would be much more effective. Do not submit pages of numbers
unless there is a really good reason -- it is not an effective way to
present the information.
- If you do print things, use
fprintf to format the output nicely instead of printing large
matrices. Also use format compact and other format commands to control
how MATLAB prints things.
Quality over Quantity
- You need to demonstrate,
in addition to a code and plot, that
you understand what the numerical problem is. For example, the
roundoff error in problem 3.1 or 3.2 comes because of cancellation of
significant digits (read the title of the Section heading!). Just
reporting "error is smallest for h=\dots" without an explanation will
not get full points. I do not expect theorems, but some understanding
is crucial.
- Do not substitute true
understanding/exploration with trivial work: Solve a few
problems well instead of handing in quarter solutions to all the
problems. Demonstrate that you are intellectually-curious about the
material.
Assignments
0. (Due ASAP) Questionnaire
Please log into Blackboard (email me for access if not registered or
there is a problem) and submit the following information (also under
Assignments on Blackboard and course webpage):
- Name, degree, and class, any prior degree(s) or professional
experience.
- List all programming languages/environments that you have used,
when and why, and your level of experience (just starting, beginner,
intermediate, advanced, wizzard).
- Why did you choose this course instead of Scientific Computing
(spring)? Have you taken or plan to take any other course in applied
mathematics or computing (e.g., Numerical Methods II)?
- Was the first lecture at a reasonable level/pace for your
background?
- What are your future plans/hopes for activities in the field of
applied and computational mathematics? Is there a specific area or
application you are interested in (e.g., theoretical numerical
analysis, finance, computational genomics)?
1. (Due Sept. 23rd, lecture on Sept. 9th) Numerical
Computing
Take a look at
lecture 1 for some
examples and possible hints.
2. (Due Oct. 7th, lectures on Sept. 16th and 23rd) Square Linear Systems
Take a look at
lecture 2 and
lecture 3 for some examples and
possible hints.
3. (Due Oct. 21st, lectures on Sept. 30th and Oct 7th) Eigen and Singular Values
Take a look at
lecture 4 and
lecture 5 for some examples and
possible hints.
Take a look at
lecture 6 and
lecture 7 for some examples and
possible hints.
Here is the
MATLAB script to compute the
Gauss-Legendre nodes on [-1,1]. Take a look at
lecture 8 and
lecture 9 for some examples and
possible hints.