Instructor: Dr. Xin Li
When: 11:30-12:20 MWF
Where: MAP 204
Lecture Notes: Please note that the notes are sometimes very sketchy. If you missed a class, make sure to get the notes of your classmates for more detailed discussion.
| Date | Lecture | Assignments |
| 4/29 | 10:00-12:50, Final Examination | Final Project due in my office: 5/4, 11:59AM |
| 4/24,4/27 | Discussion on homework and project. Review for final examination |
|
| 4/22 | Selected student presentations | |
| 4/20 | Discussion on MCMC and homework | Prepare for the Monty Hall demo (bring in your flash drive) |
| 4/17 | Project 2 background | Here's my sample Matlab code for building the first transition matrix M. |
| 4/15 | MCMC | See the notes. Here's a small text file for you to train your M matrix. |
| 4/13 | More on Monte Carlo | See the notes |
| 4/10 | Introduction to Monte Carlo method | 1. Plot the sequence {n*sqrt(2)} for n=1:1000. (Note: {x} denotes the fractional part of x.) |
| 4/8 | Face Recognition using PCA | Download the code and experiment with "recover". |
| 4/6,4/3,4/1 | SVD and PCA | As given in the notes. A sample code suing PCA |
| 3/30 | Eigenvalues and eigenvectors | 1. Revise Project I. 2. Review linear algebra |
| 3/27 | Inverse Radon (Back Projections) | See the end of the notes. I included the ppt file for you to see some of the animation that will help you to understand the computation. You need these Matlab files for some of the homework problems: rdemo.m, xbox.m, rdemoc.m, xcylinder.m |
| 3/25 | Mathematics of Medical X-Ray Image II | Verify formulas (12) and (13). |
| 3/23 | Project I working session | Helpful materials: 1. You may use a sum of translated Gaussians to generate your data set. 2. The report should follow the same format as the two sample papers but with your own words and understanding. 3. Matlab has a commend slice that can be used to help you visualize the data. Read more on slice |
| 3/20 | Mathematics of Medical X-Ray Image | Exercises 1,3,5. |
| 3/18 | paper1, paper2 | Project I: Solve MCM 1998 Problem A. (1-3 persons groups are allowed). |
| 3/16 | MRI Slicing | See the end of the notes |
| 3/6 | Maximum Matching, Max Flow | P.321: 3,4 |
| 3/4 | Shortest Path | P.321: 1 |
| 2/27 | Midterm Examination | |
| 2/25 | Review for midterm examination | |
| 2/23 | Graphs as Models | P.294: 1,2; P.297: 1. |
| 2/20 | MoG,II | See the end of the notes. For the curious, my EM tutorial is here. |
| 2/18 | Mixture of Gaussians I | See the end of the notes |
| 2/16 | Fitting data by logistic curves | See the end of the notes |
| 2/13 | Markov Chain and Linear Regression | See the end of the notes |
| 2/11 | Probabilty Models | P.220: 2,3 |
| 2/9 | Cubic splines, m-files used in class: ginterp, pop, runge, rungec, chebdiag. | Write a brief summery of the calculation of a cubic spline function that interpolates at n given points. |
| 2/4,2/6 | Model fitting | 2/4: First two problems. Please read UMAP551 before 2/6 class. |
| 2/2 | Constructing empirical models | P.137: 1,2,5 Here are sample good solutions to last week's assignments: Tim, Chris, Leon |
| 1/30 | Camera calibration | Do the assignments at the end of notes. |
| 1/28 | Modeling cameras | Do the assignments at the end of notes. |
| 1/26 | More on Hough transform | Do the 2 assignments at the end of notes. |
| 1/23 | Line detection | Do the assignment at the end of the notes. You may need this image file for your home work. |
| 1/21 | Convolution | Do the homework at the end of the notes. Here are two links you need: |
| 1/16 | Digital Image | Do the exercises at the end of the notes |
| 1/14 | Examples | P.17: #9, P.31: #1(a),(c), P.33: #3(d),(e) |
| 1/12 | Principles of Mathematical Modeling | Sect. 1.1: 1,3,5,7 |
| 1/9/2009 | Intro to Matlab, II | Do the exercises at the end of the notes. Browse through this recent article on the importance of mathematical modeling from the Notices of American Mathematical Society. |
| 1/7/2009 | Intro to Matlab, I | Do the exercises at the end of the notes |
