Information Package / Course Catalogue
Probability and Random Process
Course Code: EE466
Course Type: Area Elective
Couse Group: First Cycle (Bachelor's Degree)
Education Language: English
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 5
Objectives of the Course

The objective of this course is to approach random variables and random processes from electrical engineering point of view.

Course Content

Probability Models in Electrical Engineering, Random Variables, Random Processes, Analysis and Processing of Random Signals, Markov Chains

Name of Lecturer(s)
Learning Outcomes
1.To understand the basics of random variables and processes
2.To have knowledge on random signals in electrical engineering problems
3.To be able to model random experiments and outcomes
4.To learn representing random signals in frequency domain
5.To have knowledge about responses of linear time-invariant systems to random input signals
Recommended or Required Reading
1.Probability, Statistics and Random Processes for Electrical Enginneering, 3rd ed. by A.L. Garcia, Pearson.
Weekly Detailed Course Contents
Week 1 - Theoretical
Probability Models in Electrical Engineering
Week 2 - Theoretical
Random experiments, Conditional probability, Bayes' Rule
Week 3 - Theoretical
Types of random variables, Discrete random variables, The probability density function, The cumulative distribution function,
Week 4 - Theoretical
Continuous random variables, families of continuous random variables
Week 5 - Theoretical
The expected value of random variables, functions of random variables
Week 6 - Theoretical
Multiple random variables, joint density, distribution, and moments
Week 7 - Theoretical
Jointly Gaussian random variables, Linear transformation of Gaussian random variables
Week 8 - Theoretical
Sums of random variables, central limit theorem
Week 9 - Theoretical
Continuous and dicrete time random processes, Poisson process, Stationary random processes
Week 10 - Theoretical
Spectral representation random processes
Week 11 - Theoretical
Response of linear time-invariant system to a random input signal
Week 12 - Theoretical
The Kalman filter, estimating the power spectral density.
Week 13 - Theoretical
Markov processes, discrete-time Markov chains.
Week 14 - Theoretical
Project Presentations
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%30
Final Examination1%40
Quiz4%10
Project1%20
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory141356
Assignment2204
Project112315
Individual Work120224
Quiz4002
Midterm Examination110212
Final Examination110212
TOTAL WORKLOAD (hours)125
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
OÇ-1
4
3
4
4
4
4
4
4
4
5
4
4
OÇ-2
4
4
3
3
5
4
4
4
5
3
4
5
OÇ-3
5
4
5
5
4
4
4
5
5
4
5
4
OÇ-4
4
5
4
5
4
5
5
4
4
4
4
4
OÇ-5
4
4
4
4
3
4
4
4
4
4
4
4
Adnan Menderes University - Information Package / Course Catalogue