- TIME:
- TR 3:00 - 4:15 PM
- PLACE:
- CEC 441
- INSTRUCTOR:
-
Dr. J. P. Havlicek
CEC 432
Tel: 325-4279
Office Hours: TR 1:30 - 2:30 and by appointment
E-mail: joebob@ou.edu
- TEXT:
-
R. G. Brown and P. Y. C. Hwang, Introduction to Random Signals
and Applied Kalman Filtering: with MATLAB exercises and solutions,
3rd ed., John Wiley & Sons, New York, 1997.
Textbook Errata:
http://www.wiley.com/college/brown/0471128392/instructor.html
- COURSE WEB PAGE:
-
http://coecs.ou.edu/Joseph.P.Havlicek/Kalman/
- PREREQUISITES:
- ECE 5223
- REASONABLE ACCOMMODATION POLICY:
-
The University of Oklahoma is committed to providing reasonable
accommodation
for all students with disabilities. Students with disabilities who require
accommodations in this course are requested to speak with the instructor as
early in the semester as possible. Students with disabilities must be
registered with the Office of Disability Services prior to receiving
accommodations in this course. The Office of Disability Services is located
in Goddard Health Center, Suite 166, (405) 325-3852 (Tel)
or (405) 325-4173 (TDD only).
- RELIGIOUS HOLIDAYS:
-
It is the policy of the University to excuse absences of students that result
from religious observances and to provide without penalty for the
rescheduling of examinations and additional required classwork that may fall
on religious holidays. It is the responsibility of the student to
make alternate arrangements with the instructor at least one week prior
to the actual date of the religious holiday.
- UNIVERSITY POLICY ON ACADEMIC HONESTY:
-
http://www.ou.edu/provost/integrity
This page outlines the University's expectations of academic honesty, defines
misconduct, provides examples of prohibited conduct, and explains the sanctions
available for those found guilty of misconduct. Additional information about
the meaning of academic misconduct in this course is provided later
in this syllabus.
The UOSA Statement of Academic Integrity will be used in this course.
- COURSE DESCRIPTION:
-
This course will provide a review of stochastic processes and random signals
followed by a comprehensive development of Kalman filtering and optimal
estimation in both discrete and continuous time. Emphasis will also be placed
on modeling, practical considerations, and the development of
implementation skills.
- HOMEWORK:
-
Homework will be assigned during class.
You are encouraged to
work together on homework, but DO NOT COPY! Each problem solution
that you turn in must be your own;
if you copy another person's
solution and turn it in as your own, then you are guilty of
academic misconduct.
If you copy a homework solution from any other source and turn it in
without working the problem yourself, then you
are guilty of academic misconduct.
Some homework problems will involve computer programming.
The standards of academic honesty articulated above apply to computer-based
homework problems as well. In addition:
- All computer codes and results that you turn in as homework solutions
must be your own original work, except as noted in (4)
below.
- If you obtain code from another person in an electronic format and
incorporate it into the solution that you turn in, then
you are guilty of academic misconduct.
- If you obtain code from another person in electronic or hardcopy
format, type some or all of it in yourself, and then include this
as part of the solution that you turn in, then
you are guilty of academic misconduct.
- In certain cases, it may be acceptable to incorporate existing public
domain and/or library computer algorithms and codes into a solution
that you submit. In such cases, however, you must always obtain prior
authorization from the instructor and you must always document the source
of any algorithms and/or code that are not your own original work.
- PROJECTS:
-
There will be two substantial projects involving the design and
implementation of Kalman filters. The first project will be an individual
project. The same standards of academic honesty that apply to homework apply
to the first project as well.
The second project will be a group project. Group assignments will be made
by the instructor. The second project will be due on
the last regular class meeting of the semester.
Each group will present a written project report. This written report
can be turned in early. Each group will also make a presentation and
demonstrate their project to the class
during the final regular class meeting of the semester.
This activity will be in lieu of a final exam.
- TESTS & EXAMS:
-
There will be a midterm exam.
The midterm will be announced in class at least one
week in advance. The midterm exam will be open books and open notes.
You may use calculators on the midterm. All work that you turn in on
the midterm exam must be your own original work. At the discression of the
instructor, the midterm exam may be an in class exam, a takehome exam, or
a combination of both.
- GRADING:
-
Your final numerical grade will be calculated as shown in the following table.
| What |
Value |
| Homework |
20% |
| Midterm |
30% |
| Project 1 |
20% |
| Project 2 |
30% |
These numerical grades will be converted into letter grades using a curve that
I will determine. The same curve will be applied to everyone in the class.
The curve will never hurt you relative to the
standard ten-point grading scale.
