Syllabus Application
Random Processes
EE 550
Faculty:
Faculty of Engineering and Natural Sciences
Semester:
Fall 2025-2026
Course:
Random Processes - EE 550
Classroom:
FENS-L030,FENS-L058
Level of course:
Masters
Course Credits:
SU Credit:3.000, ECTS:10
Prerequisites:
-
Corequisites:
-
Course Type:
Lecture
Instructor(s) Information
Özgür Erçetin
- Email: oercetin@sabanciuniv.edu
Course Information
Catalog Course Description
Random processes and sequences, stationarity and ergodicity properties of auto- and cross-correlation functions, white noise, power spectral density and spectral estimation simulation of random processes, whitening, linear and non-linear estimation, and Wiener filtering.
Course Learning Outcomes:
| 1. | Solve problems about the results of random experiments using the concept of discrete and continuous random variables |
|---|---|
| 2. | Use the concept of joint probability distributions, marginal distributions and conditional distributions for multiple random variables for solving complex problems in various engineering domains that involve probability |
| 3. | Calculate and grasp the significance of the expected value, variance, and standard deviation of a single random variable and mean vector and covariance matrix of a random vector |
| 4. | Analyze random processes and characterize the response of LTI systems driven by a stationary random process using autocorrelation and power spectral density functions |
| 5. | Gain sufficient background for the subject areas of detection and estimation, communications, random signal processing, stochastic control, pattern recognition and machine learning |
| 6. |
Course Objective
Graduate level course on probability and stochastic processes. Single and multidimensional discrete and continuous random variables. Probability and moment approximations using limit theorems, basic random processes, wide sense stationary random processes, linear systems and wide sense stationary random processes, multiple wide sense stationary random processes, Gaussian random processes, Poisson random processes. Optimal linear systems.
Course Materials
Resources:
Probability and Random Processes for Electrical Engineering by A. Leon Garcia.