2008 AMSC/CMSC 660 Term Project Information
12-02-08 Notes
The assignment:
Suppose that you are the instructor for 660. Write a case study
for the class that solves an interesting application problem,
using one or more of the algorithms studied this semester.
Also write a solution for the case study, including well-documented
Matlab code.
Deadlines and points:
By November 19, you should send me e-mail with the title
and a short description of your project.
The project is due at 10 am Tuesday, December 16.
It is worth 100 points.
There will be a 15% penalty
for projects turned in up to 24 hours
late, 30% penalty for projects turned in
24--48 hours late, etc.
Model your project on the Case Study chapters in the textbook,
the corresponding chapters in the solution manual, and
the software provided with it.
A case study should typically have 4-5 challenges.
The project should include:
one or more written challenges to explore the basis of the algorithm
or the nature of the problem.
one or more Matlab challenges that solve the problem using one
or more algorithms and then evaluate the goodness of the
answers.
a discussion component.
a list of references.
How to get started:
Each person is required to have a unique project, so
tell me your idea, and I will add it to the list
of claimed topics on this page.
If you don't have any ideas, let's talk.
What to submit for the project:
The assignment, as you would hand it out to students.
The answers to the written problems, Matlab programs
(documented to the standards in Chapter 4),
any necessary data files,
and a discussion.
Also include a list of relevant references.
How to submit:
Submit your project by e-mail. The time stamp on the
e-mail will determine whether the project is on time or late.
The Matlab programs should be
in plain text, stored in files that can actually be run by Matlab.
Data files should be in .mat format.
The assignment, answers, and discussion should be in plain
text, html, pdf, or ps format.
Microsoft-formatted
documents (Word, Excel, Powerpoint, etc.) will not be accepted; submit
a pdf or ps file for these.
The entire set of files should be bundled into a single
file (in tar, zip, or gzip format) and attached to the e-mail.
My workstation runs UNIX, so Microsoft-specific features
are unlikely to work properly.
I'll acknowledge your submission by e-mail after I have successfully
extracted the files.
Some questions that will be asked while evaluating a project:
The assignment:
Is it clear and correct?
Was it spell-checked?
Does it reinforce ideas taught in the class and
make it clear why they are useful?
Does it contain written questions and programming?
Is the application explained well to a novice?
Do the students have all of the information they need
to complete the assignment?
Is it appropriately difficult for 660 students?
Is it interesting and novel?
If appropriate, are references given where a student
could go for more information?
Do the students learn important lessons by completing
the assignment?
The answer:
Is it clear and correct?
Was it spell-checked?
Are the Matlab codes well designed and well documented?
Warning:
The only failing grades I have given on this assignment have been for
lateness or
plagiarism. If you use someone's ideas, cite the source.
If you use a direct quote, use quotation marks and cite the
source. And don't expect a good grade on a project that is
mostly someone else's work.
A note on formatting:
The format for your project does not need to be the same as the
homeworks that I have given you, but here is a Latex template
(which uses the class file found here ) and the resulting pdf output ,
in case you find it useful.
If you can't think of a topic, here are some ideas to consider:
Solve an optimal control problem using variants on
methods discussed in the book.
Form and solve an ecological model.
Give an application of semidefinite programming and solve the problem.
Present parallel algorithms for factoring matrices.
(One person could consider vector processors while another considered
a network of connected processors.)
Present an application of surface fitting and (stable) algorithms to do it.
Present an application of multidimensional integration and solve it.
Present an application that produces a system of nonlinear equations
and solve it.
Projects chosen by other students this semester and in previous
semesters:
Your project must be different from
all of these, so either pick a different topic or
check with me to make sure that your ideas are
sufficiently different from what these students did.
This semester:
Speech analysis and
modeling based on rotational invariant techniques (ESPRIT)
Toeplitz matrices and least squares problems
A Comparison of Clustering Algorithms for Gene Expression Microarray
Data
Image Segmentation using Spectral Clustering Methods
Failure prediction of MLCCs under temperature-humidity-bias testing
conditions
Motion of 2 and 3 particle systems in a central force
A Monte Carlo Approximate SVD
Evolutionary Game Equilibrium Points/Opponent Modeling in a Negotiation Game
Non-linear PCA for feature selection and clustering
Inverse Kinematics for Redundant Robotic Manipulators
Optimization for guardian placement on campus
Expectation-Maximization algorithm and
Image Segmentation
Numerical solution of boundary value problems in chemical vapor deposition reactor systems
Product Sales Estimations using Monte Carlo methods
Use of the improved fast Gaussian transform in linear
system solving
Monte Carlo and finite differences in option pricing
Monte Carlo methods in natural language processing
Digital photography post-processing
Social learning strategies
Photon mapping with Monte Carlo
Contaminant Source Reconstruction Using Monte Carlo
Techniques
Approximating images with wavelet dictionaries
Circuit Analysis of Winner Take All (WTA) networks
Monte Carlo
simulation of a vapor deposition process: minimizing
surface roughness
Direct Linear Transformation of 2D
Images
Estimation of Characteristics of Ellipsoid Shaped Objects
ODEs in solving first-price auctions
Previous semesters:
Use variants of latent semantic indexing (SVD and other decompositions)
to perform document retrieval.
Perform image compression using various matrix-based approaches.
Present the fast multipole algorithm in matrix terms and
solve a problem using it.
Survivable Network Design
Formulate the data assimilation problem
in meteorology in terms of our matrix factorizations.
Use wavelets to approximate a signal, and compare with Fourier
analysis.
Designing a helicopter seat to damp vibration
Illustrate the role of unitary matrices in quantum computing.
Analysis of poker
Support vector machines
Mobile emergency communcation
Derivative-free methods for constrained optimization
Solution of convection-diffusion equation using ODEs
Protein folding using homotopy methods
Monte Carlo models of raindrops
Hydro-mechanical Analysis of a Magnetorheological Energy Absorber (MREA)
with Bifold valves for Shock Load Mitigation
Plasma physics particle simulation
Independent component analysis
Monte Carlo for Markov chains and Bayesian Networks
Parallel Algorithms for Scalar Product and LU
Decomposition
Health diagnostics and performance diagnostics of electronic
systems
Linear rational equations
Location estimation using gps
Solving the human heart dipole problem
using tabu search
FIR eigenfilters design
Kalman filtering, linear and nonlinear
Face recognition by PCA
Metropolis algorithm for finding independent sets in a graph
Simulated annealing for particles with Lennard-Jones potential
Neuronal layout optimization
Maximum entropy design of computer experiments
CMOS circuit optimization using geometric programming
Preconditioning conjugate gradients
SVD filtering for video images
ODE models of structured population dynamics
Metropolis for DSP address optimization
Spectral clustering methods for image segmentation
Solution of the secular equation
Monte Carlo description of a dynamic terrain
A Metropolis-based algorithm for solving the Prisoner's Dilemma
Singular value analysis of cryptograms
Handwritten Postcode recognition by PCA
Document clustering through matrix factorization.
epipolar alignment of stereo cameras
Finding Fundamental Matrix for Stereo Vision
minimizing helicopter vibration using flap control