| Lecture | MW 3:30 - 4:45, KEB 1110 |
| Discussion Sections |
0101: F 9:00 - 9:50, EGR 3102
0102: F 10:00 - 10:50, EGR 2103 FR01: TBA |
| Required Texts | Roy D. Yates and David J. Goodman, Probability and Stochastic Processes (2nd edition), Wiley, 2004, ISBN: 978-0-471-27214-4. |
| Required Software | MATLAB (see below for details) |
| Prerequisites |
ENEE 322 (Signal and System Theory)
Completion of all lower-division technical courses in the EE curriculum |
| Web Site | http://terpconnect.umd.edu/~jzsimon/enee324/ (Recorded lectures, but nothing else, will on BlackBoard: https://bb.eng.umd.edu/.) |
| ECE Description | http://www.ece.umd.edu/Academic/Under/ucourses1.htm#ENEE%20324 |
| Testudo Info | http://www.sis.umd.edu/bin/soc?crs=ENEE324&sec=&term=201101 |
| Professor | Jonathan Z. Simon |
| ECE Office: | AVW 2209 |
| ECE Phone: | 301-405-3645 |
| Bio Office: | BPS 3227 |
| Bio Phone: | 301-405-6812 |
| Email: | jzsimon@umd.edu |
| URL: | http://www.isr.umd.edu/Labs/CSSL/simonlab/ |
| Future Faculty Fellow | Matthew C. Stamm |
| Office: | KEB 2242 |
| Phone: | 301-405-0470 |
| Email: | mcstamm@umd.edu |
| URL: | http://www.ece.umd.edu/~mcstamm/ |
| Teaching Assistant | Ashish Shrivastava |
| Phone: | ashish@umd.edu |
| Teaching Assistant | Michael Jones |
| Phone: | jones.michael.william@gmail.com |
| Day | Time | Location | |
|---|---|---|---|
| Simon | Thu | 3:00 - 5:00 | AVW 2209 |
| Stamm | Tue | 2:30 - 3:30 | KEB 2242 |
| Shrivastava | Fri | 1:45 - 2:45 | AVW 4473 |
| Jones | Fri | 11:00 - 12:00 | AVW 2448 |
The following topics will be addressed (order, emphasis, and duration are tentative):
Topic Sample Space and Events Axioms of Probability Computing Probabilities Conditional Probability and Independence Sequential Experiments Random Variables Some Important Random Variables Functions of a Random Variable; Expected Value Transform Methods Introduction to Multiple Random Variables More About Means and Covariances Conditional Distributions and Conditional Expectation Functions of Several Random Variables Engineering Statistics Introduction to Random Processes Stationary Random Processes
Math is a “Learn it By Doing it” subject. The homework assignments are truly critical parts of the course: you will not be able to handle the exams if you don't learn from the homeworks.Typically, homework problems will be assigned every Monday and due the following Monday. It is possible that only some of the problems will be graded, without prior notification of which problems it will be.
Solution sets will be handed out as soon as reasonably possible after the homework is due, so there are stiff penalties for late homework:
Homework grades have a half-life of 1 weekday.
For example:
In addition, no credit will be given for any homework turned in after the solution set has been made available (typically 2 days after the deadline).
- 1 weekday late: score is multiplied by 50%
- 2 weekdays late: score is multiplied by 25%, etc.
Discussion sections will be run by the TA. During these classes, selected homework problems as well as other problems will be discussed, and students will have an opportunity to ask clarifying questions concerning the class material.
At the discussion section following the homework due date, students may be asked to take an unannounced written quiz wherein they will be required to solve, without notes, a problem closely related to one from that homework set. Several quizzes may be given during the course of the semester.
- 1st Exam: Wednesday March 16 (confirmed)
- 2nd Exam: Wednesday April 27 (tentative)
- Final Exam: Saturday, May 14 1:30-3:30 pm
There will be no make-up exams. See Grading next for missed exam policies.
Homework, quizzes,and class participation 30% 1st exam 20% 2nd exam 20% Final exam 30% In the case of a missed 1st or 2nd exam, the weights of the other exam and the final will be modified accordingly, if you give notice to the professor within 24 hours of the missed exam:
1st or 2nd exam 28% [ = (20%/(20%+30%)) x 70% ] Final exam 42% [ = (30%/(20%+30%)) x 70% ]
If you do not request permission for this modified grading within 24 hours of the missed exam, you will receive zero for the missed exam.
A MATLAB primer is available. You will need to be able to run and print from MATLAB (any version from 5 up will do).
There are many computers around campus with Matlab installed. OIT can display which open labs have Matlab here. (For the purposes of this course, it should not matter which version of Matlab is installed.) Additionally, if you want to buy the (fully functional) student version of Matlab, it is $99 at most places (for some reason it's $109 in the campus bookstore). This is a good deal, compared to the full version.
Discussing homework problems, and other ideas, with others is encouraged,
but,
your final write-up must be your own work and cannot be a copy of anyone else's work.The University of Maryland, College Park has a nationally recognized Code of Academic Integrity, administered by the Student Honor Council. This Code sets standards for academic integrity at Maryland for all undergraduate and graduate students. As a student you are responsible for upholding these standards for this course. It is very important for you to be aware of the consequences of cheating, fabrication, facilitation, and plagiarism. For more information on the Code of Academic Integrity or the Student Honor Council, please visit http://www.studenthonorcouncil.umd.edu/whatis.html.
It is in everyone's best interest that these policies are clear and explicit. Academic dishonesty, in this class, includes copying homework answers from any other student's work, from any solution sets, from any book, from the web, etc..
Instances of academic dishonesty are referred to the Office of Judicial Programs.
All students will be asked to write and sign the honor pledge at every exam.
If you are experiencing difficulties in keeping up with the academic demands of your courses, you should know about the Learning Assistance Service, 2201 Shoemaker Building, 301-314-7613. They have educational counselors to help with time management, reading, note-taking, and exam preparation skills.
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