MATH3423H Seminar - II

Term                   : Winter, 2013
Lectures               : Tuesday, 4:40 pm - 6:15 pm
Location               : LSB, G34

Course website: http://www.math.cuhk.edu.hk/~jwong/mat3423h

Instructor: Dr. Jeff Chak-Fu WONG
E-mail: jwong@math.cuhk.edu.hk
Office: Room 208, LSB
Phone extension: 2609 - 7987
Lecturer's office hours: Monday-Wednesday-Friday - 1:30 - 2:30 pm, or by appointment.

Announcements

                                                                                                                                                                                                                                                Back to top

Aim

The objective of this seminar is to provide students with an understanding of particle filter and data assimilation used in bioinformatics. Bayesian network and estimation theory are a very broad concept and we will focus on issues related to DNA, protein sequence analysis, evolutionary models and phylogenetic tree estimation.

Text Books & References

Optimal state estimation : Kalman, H. [infinity] and nonlinear approaches, 1st Edition  (c) 2006 by Dan Simon, John Wiley.

Introduction to Random Signals and Applied Kalman Filtering: with MATLAB Exercises and Solutions, 3rd Edition  (c) 1996 by Brown, Robert Grover Hwang, Patrick Y.C., John Wiley & Sons, Inc.

Data Assimilation: The Ensemble Kalman Filter, 1st Edition  (c) 2006 by Geir Evensen, Springer.

Format of the seminar

• The seminar, which last for about 14 weeks, will be chopped into two sections. We will have an elementary discussion of  bayesian network and estimation theory in Section 1. The core of the seminar goes into Section 2. We will discuss some applications of  bayesian network and estimation theory .
• Each student has to present twice. Once in Section 1 and once in Section 2. Each presentation will last about 1 hr 30 mins. 
• Students will have at least 20 mins to summarize your report on 16th/23th April, 2013.  Each student must submit a full report on 30th April, 2013.
  

Time Schedule

January 2013

February 2013

March 2013

April 2013

May 2013

                                                                                                                                                                                                                                    Back to top