AMSC/CMSC 660 Term Project Information

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.

Deadlines and points:

  • By October 31, you should send me e-mail with the title and a short description of your project.
  • The project is due at 12 noon, Friday December 15.
  • 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 studies in the book. In particular, the first drafts of Chapters 11, 12, and 24 were term projects in this course.

    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 evaluates 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, a Matlab program (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.
  • 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 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 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:

  • 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
  • Previous semesters:

  • SPSA for optimization in contact motion analysis
  • Randomized Gauss elimination
  • Watermarking documents using SVD
  • Kalman filtering, linear and nonlinear
  • Trajectory extraction from images using region growing and optimization
  • ODE-based neuron models
  • Face recognition by PCA
  • Sensitivity analysis for a integrated subthreshold MOSFET circuit.
  • Generating signature sequences for wireless communication
  • Metropolis algorithm for finding independent sets in a graph
  • Positive matrix factorizations for document clustering
  • 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
  • Correcting phase-distortion in adaptive optics by optimization
  • Monte-Carlo for American-Asian option pricing
  • SVD filtering for video images
  • ODE models of structured population dynamics
  • Metropolis for DSP address optimization
  • Modeling distances in large-scale networks by matrix factorization
  • Spectral clustering methods for image segmentation
  • Solution of the secular equation
  • Parameter extraction for MOSFETs using nonlinear least squares kobyakov
  • Queueing models of networks

  • Monte Carlo methods for the stable marriage problem
  • Monte-Carlo simulations for zeta potential in electroosmosis
  • Monte Carlo methods for option pricing
  • Monte Carlo simulation of Nucleation
  • Monte Carlo description of a dynamic terrain
  • A Metropolis-based algorithm for solving the Prisoner's Dilemma
  • Refine Traveling Salesperson Solution by using Metropolis algorithm
  • Metropolis algorithm for data partitioning and query scheduling

  • Denoising sound recordings through SVD
  • Singular value analysis of cryptograms
  • SVD for document retrieval
  • SVD and polar decomposition in robotics
  • SVD for image compression and restoration
  • Ensemble weather forecast inflation using the SVD
  • Handwritten Postcode recognition by PCA
  • PCA and storage of face images

  • Document clustering through matrix factorization.
  • ESPRIT algorithm for finding direction of arrival of signals
  • Rotation Sequences with Euler Angles versus Quaternions
  • epipolar alignment of stereo cameras
  • Finding Fundamental Matrix for Stereo Vision
  • Stability analysis of optimal robotic control

  • minimal surfaces (integral equation approach)
  • Approximate solutions to NP-hard problems through semi-definite programming and related methods
  • least squares in reducing rotocraft noise
  • Fitting lines using least squares, total least squares, and E-M
  • capacity maximization for wireless communications
  • comparison of optimization methods for optimal control
  • trajectory optimization for minimizing fuel consumption
  • minimizing helicopter vibration using flap control
  • Design of smoothing filters
  • signal synchronization in airborne gravitational measurements
  • Parameter Estimation Schemes for Damped Sinusoidal Signals
  • Solving quadratic programs using gradient projection methods
  • IsoClus clustering algorithm
  • Training of a Artificial Neural Network as an Optimization Task
  • Support Vector Machine for Pattern Classification

  • homotopy method to find periodic solutions to a nonlinear differential equation
  • Schroedinger equation for 2 electrons on an interval
  • Finite Difference Method for the Heat Equation
  • using finite differences to solve supported rotating beam problem
  • Couette flow
  • A simple micromagnetics simulation using ODE

  • identifying shapes in images using active contours and minimization
  • Jacobi's computation of planetary orbits

  • Error concealment for block transform coding image
  • Newton's method for nonlinear systems
  • Measuring Image Similarity Based on Local Edge Direction