4503 ECEN Random Signals and Noise Spring 2004 Syllabus
Time: Place: Prerequisite: Tuesday/Thursday 5:00-6:15 PM Engineering South 214A Completeion of the junior block courses, in particular this course builds on the material covered in ECEN 3513- Signal Analysis and ECEN 3723- Systems I Probability, Random Variables and Random Signal Processing 4th edition, Peyton Z. Peebles, Jr., McGraw-Hill, 2001 Probability, Random Variables, and Stochastic Processes A. Papoulis, McGraw-Hill, 1965 Probability amd Random Processes, An Introduction for Applied Scientists and Engineers W.B. Davenport, Mc-Graw-Hill, 1970 An Introduction to Probability and Stochastic Processes J.L. Melsa and A.P. Sage, Prentice-Hall, 1973 Probability and Stochastic Processes for Engineers C.W. Helstrom, Macmillian, 1984 Professor Gary G. Yen, Engineering South 404
http://www.okstate.edu/elec-engr/faculty/yen
Text: References:
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Instructor:
405-744-7743, 405-744-9198 (fax), [e-mail] Office Hours: Tuesday/Thursday 9:00AM-12:00PM; or by appointment only TA: Objectives: TBD (weekly homework help session) Introduce some basic principles of probability, random variables and random signals to deal with system involving random process and noise through mathematical analysis and computer simulations. The topics include Probability theory o set definition; set operations; joint and conditional probability; independent events; Bernoulli trials Random variable o basic concept; discrete/continuous/mixed random variables; distribution function; density function; Gaussian random variable; Binomial/Poisson/uniform /exponential/Rayleigh random variables; conditional distribution/conditional density function Operations on one random variable
o expectation; moment; transformation of a random variable; computer generation of random variable Multiple Random Variables o vector random variables; joint distribution/marginal distribution; joint density/marginal density; conditional distribution/conditional density function; statistical independence; distribution and density of a sum of random variables Central Limit Theorem Operations on multiple random variables o expected value of a function of random variables; joint Gaussian random variables; linear transformation of Gaussian random variables; computer generation of multiple random variables Random process o basic concept; classification of random processes; first-/second-order stationary process; wide-sense stationarity; n-order and strict-sense stationarity; time average and ergodicity; auto-correlation/crosscorrelation function; covariance; Gaussian random process; random Poisson process Spectral analysis of random processes o power density spectrum; bandwidth; cross-power density spectrum; noise deinfition; white and colored noises Linear Systems with random inputs o linear system; transfer function; random signal response; spectral characteristics; noise bandwidth; modeling of noise sources; noisy network 20%
Grading:
10 Weekly Homework Assignments Tentative schedule1/22, 1/29, 2/5, 2/12, (before the first midtem) 3/2, 3/9, 3/23, 3/30, (before the second midterm) 4/15, 4/22 Computer Simulation Project Midterm Exam 1 (February 24, 5:00-6:30 PM) Midterm Exam 2 (April 8, 5:00-6:30 PM) Final Exam (May 4, 6:00-7:50 PM)
10% 20% 20% 30%
A-88% above; B-76%-88%; C-66%-75%; D-56%-65%; F-55% below
Note: Drop and Add:
All exams are open notes, but close book. The instructor will follow University, College and Departmental guidelines for drops and adds. Consult the
calss schedule book or Ms. Helen Daggs in Engineering South 202 for more information. Attendance: Attendance record will be sampled randomly and will be counted toward your grade. Students will be expected to attend class. Habitual failure to do so will result in a reduced grade. Class attendance is taken occasionally for reference. An incomplete grade will only be given when a student misses a portion of the semester because of illness or accident. All (I) grades must be completed within thirty days. Academic Dishonesty: Cheating on homework, quizzes, project or examinations, plagiarism and other forms of academic dishonesty are seri...