EEL 6545 RANDOM PROCESSES IN ENGINEERING

Instructor: Prof. Dave Snider, ENB 362, 813-9744785, snider@eng.usf.edu, office hrs. TBA

Lecture Material: Fall 2004: Lecture for Sept. 8th - PDF

Catalog Description: Review of probability theory, functions of random variables; examples in electrical engineering. Sequences of random variables. Concepts in random processes, correlation functions, power spectrum, random inputs to linear systems. Spectral analysis. Applications to engineering systems.

Semesters Offered: Fall

Course Prerequisites: EGN 3443 or equivalent first course in statistics (laws of probability, Bayes's theorem, probability density function, moments)

Course Corequisites: none

Courses that require this as a direct prerequisite: none

Level: G Credits: 3 Class Time: 3 hours lecture

Text (Recommended, not required): Statistical Digital Signal Processing and Modeling

Author: Monson Hayes

Publisher: John Wiley and Sons

ISBN: 0-471 59431-8

Reference (supplemental reading): none

Course Objectives:

1. Students review basic probability and statistics (Criterion 3(a)).

2. Students learn methods of classifying, analyzing, and simulating random processes (Criterion 3(a)).

3. Students study applications to engineering (Criterion 3(a)).

Topics and (# of Lectures):

1. Basic probability and statistics review (6)

2. Vector random variables and moments (6)

3. Random processes (8)

4. Mean-square calculus (10)

5. Stationary processes and sequences (8)

6. Spectrum Estimation (6)

Specialization: This is an elective course open to all engineering graduate students. Class size is typically 65, including FEEDS students

Additional Course Features:

1. Course is offered to remote sites via FEEDS network.

2. Course is Web-enhanced. Certain tests, assignments, and downloadable supplementary materials will be available and graded at the Web site, to be announced.

See instructions below on how to access the site.

3. Each student must email Prof. Snider by the second week. The message must contain the following:

Last name: ______ First name: _______ Class: EEL 6545 IEEE member (yes, no)

Thereafter each student is liable for all email notices concerning the class from Prof. Snider.

Relation of Course to EE Dept. Program Objectives and Outcomes: 1(a), (c)

Assessments:

1. A diagnostic test, assessing the student's preparedness for taking this class, will be administered and graded through the class web site. In order to pass the course each student must retake this test until a score of 100% is achieved. This task should be completed before the end of the first week of classes, in order that the student can drop the class without financial loss if he/she is insufficiently prepared; in any case, the task must be completed by the end of the second week of classes.

Instructions for taking the diagnostic test will be announced at the first class.

2. Certain assigned problems will be identified as graded homework; answers will be submitted to the web site, and graded with recommendations for resubmission. Partial credit will be awarded.

3. Other homework problems will be recommended to the students, but not graded.

4. A midterm examination and a final will be given. The format and dates of these exams will be determined during the semester.

Typical Grading: email assignment pass/fail, diagnostic pass/fail, graded homework 25%, midterm (25%), final (50%).

Actions Taken to Improve the Course: Web-course enhancement, new prerequisite.

Standard Syllabus Prepared by: Snider

Date of Approval of Standard Syllabus by Area: Aug. 27, 2000