ELEC 471: Random Signals and Noise
Bucknell University, Spring 2003

Overview:

This is an introductory course in probability and statistics for undergraduate and graduate students. Our goal is to study and understand the basic concepts and tools of probability and statistics. We will try provide hands-on experience with the course material through demonstrations and projects using MATLAB. We will also strive to convey the relevance and usefulness of probability and statistics in practical engineering problems.

Instructor and Office Hours:

Richard J. Kozick
Office: Room 220 Dana
Phone: (570) 577-1129
FAX: (570) 577-1822
Email: kozick@bucknell.edu
Web: http://www.eg.bucknell.edu/~kozick

Office hour schedule for Spring, 2003 is M 11-12 and 3-4, T 10-11 and 2:30-3:30, W 3-4, and R 11-12.
Other times can be arranged - talk to me in class, send email, or call.
(Refer to the course home page for the most up-to-date office hours.)

Prerequisites:

MATH 211 (multivariable calculus) and ELEC 320 (Signals and Linear Systems), or equivalent.

Required Textbook:

Probability and Stochastic Processes: A Friendly Introduction for Electrical & Computer Engineers, Roy D. Yates and David J. Goodman, John Wiley Publishers, 1999.

** PLEASE BRING THE TEXTBOOK TO CLASS **

Other Books:

Many books are available on the subjects of probability and statistics. The books take many perspectives: some are mathematical, while others are oriented toward engineering, science, business, social science, etc. I can recommend other books with an electrical engineering flavor, if you are interested.


Course Home Page:

The home page for the ELEC 471 course is located at the URL
http://www.eg.bucknell.edu/~kozick/elec47103
It can also be accessed by following the link from my home page at
http://www.eg.bucknell.edu/~kozick

The course home page contains the homework assignments, syllabus, sample MATLAB programs, and other course information.

Grading: 

8 to 10 quizzes (<= 20 minutes)           20%
2 1-hour exams at 15% each                30%
Final exam                                20%
Homework and projects                     20%
Presentations                             10%
The grading will be objective, so you will be evaluated with respect to an absolute scale rather than in comparison with your classmates. There are no limits on the number of A's, B's, etc.

Graduate students will be given additional assignments.

Quizzes and Exams:

We will have two one-hour exams on the following dates:
Exam 1: Tuesday, February 25, 2003           Exam 2: Tuesday, April 1, 2003

We will also have approximately 8 to 10 short quizzes during the semester. These quizzes will follow closely with the material from the previous class sessions and the homework assignments. Missed quizzes cannot be made up, so it is important that you attend all class sessions.

Some quizzes and exams may require you to use MATLAB. The course will conclude with a final exam.

Homework, Projects, and Presentations:

Homework will be assigned weekly. A subset of the homework problems will be collected and graded. You are responsible to understand all of the homework problems, since the quizzes will be based primarily on the homework assignments and class notes.

There will also be "project" assignments that provide hands-on experience with the course material, often involving processing with MATLAB.

Each student will be asked to prepare at least one presentation to the class. The presentations will be done in groups of 2 or 3 students, and I will assign the groups and the topics. In many cases, the groups will present their solution to a homework problem. Your presentation should be well-prepared and clear.

Late homework and project assignments will not be accepted, since we will review the solutions during class on the due date. You are encouraged to work on the homework and projects with groups of your classmates. However, the work that you submit for grading must be written individually.


Course Topics:

Our goal is to study the following topics related to probability and statistics. In the Yates/Goodman text, we will study chapters 1-5 and selected topics from chapters 6, 7, 9, and 10. Above is my "wish list" of topics for the ideal course. I am certain that we will not be able to discuss everything on the list. Indeed, the last three topics in the list are typically covered in about five graduate-level EE courses!