Math 310
see Syllabus at
www.dms.uaf.edu/M310SyllF09.htm
Fall 2009 (Bueler)

Your Math 310 Individual Project

Overview:

Suggested subjects:

  1. IEEE 754 standard for floating point computations (section 2.1 is too old and confusing)
  2. computing roots of polynomials (3.5)
  3. complex Newton's method (3.5)
  4. least squares for solving overdetermined linear systems
  5. QR factorization and the Gram-Schmidt method
  6. Cholesky factorization (4.2)
  7. matrix norms and condition number (4.4)
  8. iterative refinement (4.5)
  9. iterative numerical linear algebra methods (4.6)
  10. numerical eigenvalue methods (5.1)
  11. SVD decomposition of matrices (5.4)
  12. Hermite interpolation (6.3)
  13. B splines (6.5)
  14. multi-variable polynomial interpolation (6.10)
  15. trigonometric interpolation (6.12) and the Fast Fourier Transform (6.13)
  16. Richardson extrapolation (7.1)
  17. Romberg integration (7.4)
  18. adaptive quadrature (7.5)
  19. multistep ODE solvers (8.4)

To do:

Step one is to decide on a subject that interests you.  Look at the Kincaid&Cheney textbook only as one possible source.  It is very likely there is a better, easier-to-read source.  See Moler for a "light" and practical view.  Look at wikipedia pages.  Perhaps see Numerical Recipes, an online text at http://www.nrbook.com/a/, or go to the library to find one of many numerical analysis texts.

Step two
is to get feedback from me, by turning in a proposal on Wednesday 11/25. You are also encouraged to email me at any point with ideas or questions.  I will return your proposal with comments and suggested alterations.

Step three
is to set-up a standard outline of what to do, interpreting each of these appropriately for your topic:
  1. State the problem or class of problems.
  2. Describe an algorithm or a couple of algorithms (more than two is generally unnecessary and/or unwise).  This may involve writing a code, but that is not always required.
  3. Give at least one example showing how it works.  This may involve applying the code, or doing a small version by hand and then a big version by the code, but for sure you need a worked example, and two are usually appropriate.
  4. Evaluate the algorithm:
The parts of item 4 are numerical analysis, and numerical analysis is required in your project.  Perhaps this means a theorem to state, but in any case it means careful mathematical arguments about the properties of the problem and the algorithm(s).

Step four
is to do what you have outlined.  It may be that you discover the need to do things a different way, once you actually start working on it.  If such an issue comes up and it is a significant change to the plan given in your proposal, please let me know, for instance by email.


Ed Bueler’s office Chapman 301C; phone 474-7693; email elbueler@alaska.edu; web page  http://www.math.uaf.edu/~bueler/.