EML 6934 ( Section 6385 ) -- Optimal Estimation -- Fall 2009

Class meeting time: MWF, period 4 (10:40- 11:30 am)

Class meeting place: MAE-B 229

Instructor: Dr. Prabir Barooah

• Announcements

  course flyer

  course syllabus

• No class on Wed, Oct 14 (I'm on travel), we'll arrange for a make up later.
• Projects - here's an announcement regarding the project, the document will be updated with more suggested projects (Oct 23)

• Homework

  • HW 1 (assigned: Aug 24, Due: Aug 31)

    solution to HW1

  • HW2 (assigned: Sep 2, Due: Sep 9). Here's an example MATLAB script for Problem 3.

  solution to HW2

  • HW3 (assigned: Sep 11, Due: Sep 18)

  solution to HW 3

  • HW4 (assigned: Sep 18, Due: Sep 25)

  Deadline for submission of HW 4 has been extended to Monday, Sept 28.

  solution to HW4 (problems graded: 1,2,4,5. max score: 70)

  • HW5 (assigned: Sep 25, Due: Oct 2)

  solution to HW5 (problems graded: 1, 4.3, 4.4, max score: 50)

  • HW6 (assigned: Oct 5, Due: Oct 9)

    solution to HW 6 (problems graded: 1,2, 4, max score: 45)

  • HW 7 (assigned: Oct 12, due on Monday Oct 19)
    matlab scripts for HW7:

    systemID_example1.m
    secondorder_simulation.m

  • HW8 (assigned: Oct 23, due: Oct 30)

    solution to HW8

  • HW9 (assigned: Nov 2, due: Nov 9)

  solutions to HW9

  • HW10 (assigned: Nov 20, due: Dec 2)
    
    code for HW10:

    the MATLAB files for Problem 4:

    the .m file

    funtion 1

    funtion 2

    funtion 3

• Tests

  • First mid-term: Monday, Oct 5, in class (10:45-11:30 am). Will be based on material covered in class till Sep 25 (in other words, HW 1-5). The test will be open notes and open book. You are allowed to bring your own notes (but not someone else's) and any book you please. Please bring a calculator.
  • Second mid-term: Friday, Nov 13, (45 minutes, starting at 10:45 am). open lectures notes, but closed everyting else. Test will be based on material covered till Oct 30. That is, from Hw1 to HW9.

• Resources

  • system ID with noisy data results
  • Notes on probability and random variables (updated with corrections on Sep 21)
  • Notes on Recursive Least Squares
  • Notes on derivatives involving vectors
  • A tutorial introduction to estimation and filtering, by Ian Rhodes (uploaded on Oct 19)
  • Notes on continuous and discrete-time stochastic process, Kalman filtering for target tracking (Handout #2)
  • Notes of the Extended Kalman Filter

  ___________________________________________________________________________________

  • Lecture notes from the last time the course was offered (Spring 2008). These notes were taken by one of the students in the class, but they do not come with any "warranty" of any sort from me. I am making them available to you so that you can get an idea of what kind of material is covered in this class.
  • scanned copies of the Spring 2008 feedback provided by the students in their course evaluations.
  • Tests from Spring 2008
    • mid term 1
    • mid term 2
  • Learning MATLAB from T. Green
  • An introduction to logic