Math 309 Course Notes - Adam Oberman Math

Math 309 Course Notes

Contents

Motivation

Link to the netflix prize story

Notes from week One

Notes from week two and three

Notes from Week three

Week Four and Five

We finished Ch 3. This ends the material which will be covered on the midterm. Some additional Media:NotesonLinearAlg.pdf

Week Six and Seven

Here are the examples from class. You first need to

We also refer to section 6.3 of Boyd's textbook, which you can download at http://www.stanford.edu/~boyd/cvxbook/ or just download Ch 6 File:BoydCh6.pdf

We discussed:

  • norms which measure Fidelity (the two norm) and norms which measure "noisyness" the one norm of the derivative of the signal.
  • we illustrated with examples why the "noisyness" norm is large for noisy signals, but not large for piecewise constant signals.
  • we set up a table with the two norms, illustrating how the sum of the fidelity norm and noisyness norm should denoise a signal.
  • we all talked about the differences between the one norm and the two norm, as well as the norm of the second derivative of the signal.
  • HW problems pursue these topics further.

Week Eight

More theory. The deniosing examples involved projections onto convex sets. The support vector machines (recall Griva 1.7.2) involve separating convex sets. This week we will explore geometric, computational, and analytic approaches to these problems. References are:

  • Class notes
  • Griva Sec 1.7.2 (Motivation)
  • Griva Ch 14.
  • Boyd Sec 8.2.

Week Nine

Monday was a research talk by Jack Xin which used optimization to solve problems in signal processing. The applications were: finding chemical spetra using peaks and separating two stereo sound signals for hearing aids.

Thursday: we will discuss general conditions for minima for constrained optimization problems following Griva.

Matlab code for week 9


Week Ten

Check out a contest, with 2000 Euros in prizes. This looks like it could be solved using methods from our class.