MAT 132A Syllabus Page (Winter, 2001)

Instructor: Naoki Saito
Office: 675 Kerr
Email: saito@math.ucdavis.edu
Office Hours: MW 1:30pm-3:00pm or appointment by email

Teaching Assistant: Momar Dieng
Office: 466 Kerr
Email: momar@math.ucdavis.edu
Office Hours: T 10:00am-11:00am, Th 3:00pm-4:00pm, or appointment by email

Course Description:
    This course introduces the most useful stochastic processes in practice, such as Markov chains, Poisson processes, and assorted applications selected from Markov Chain Monte Carlo methods, Hidden Markov Models, or Brownian motion.  I also plan to cover important applications of Markov  chains to:

• Speech recognition and Hidden Markov Models
• Image processing and modeling
• Geology and geophysics

• Required: S. M. Ross, Introduction to Probability Models, 7th edition, Academic Press, 2000.
• Optional: P. Bremaud, Markov Chains, Springer-Verlag, 1999.

• Chapter 3: Conditional Probability and Conditional Expectations
• Chapter 4: Markov Chains
• Chpater 5: The Exponential Distribution and the Poisson Process

Prerequisite:

• MAT 131, STA 131, or equivalent, i.e., the prospective students should be familiar with the basic probability theory.
• MAT 22A, i.e., the basic linear algebra.

• Regular attendance to the lectures is strongly advised.
• Neither eating nor disturbing the lectures/the other students is allowed.

I will maintain the  Web pages for this course (one of which you are looking at now).  All homework assignments and important announcements will be posted on these pages.  Please check these pages regularly.
You can access the 132A home page at https://www.math.ucdavis.edu/~saito/courses/132A/

• 30% Homework
• 30% Midterm
• 40% Final Exam
• Overall grade will be based on the distribution of the weighted sum of these scores.

Midterm exam is scheduled on Feb. 16(Fri)  in class (12:10pm-1:00pm).

The final exam will be held on Mar. 20 (Tues) from  8am to 10am at the same room 108 Hoagland.

There will be NO MAKE-UP EXAMS for Midterm and Final. If you miss exams due to unavoidable circumstances such as serious illness of yourself or death in your family, you must provide me with a written proof and document. Then I will adjust the weights to the exams you actually took to make the sum of the weights 100%.

I will assign homework every Friday. Its due date is the following Friday. I will collect the homework at the beginning of the Friday lecture.  LATE HOMEWORK WILL NOT BE ACCEPTED. A subset of these problems will be graded. The graded homework will be returned in the class about a week later after the submission. The solution will be posted as pdf file in the homework page.
Click here to go to the homework page.

Note that there will not be class on Jan. 15 (Mon) and Feb. 19 (Mon). To make up these, there will be an additional class on Mar. 15 (Thu) as the registration guide describes.