COURSE INTRODUCTION AND APPLICATION INFORMATION


Course Name
Stochastic Processes
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
EEE 652
Fall/Spring
3
0
3
7.5
Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
Third Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives
Learning Outcomes The students who succeeded in this course;
  • be able to determine the probability density function and calculate probability,
  • be able to identify the parameters of discrete and continuous random variables,
  • be able to determine the characteristics of the sum of the random variables,
  • be able to do hyphothesis testing based on the random observations,
  • be able to determine the autocorrelation and power spectral density of random signals,
  • be able to obtain the best estimate based on the random measurements,
  • be able to determine the Markov Chain model of random processes,
Course Description
Related Sustainable Development Goals

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Review of Probability Text Book (Ch. 1)
2 Discrete Random Variables Text Book (Ch. 2)
3 Continuous Random Variables Text Book (Ch. 3)
4 Pairs of Random Variables Text Book (Ch. 4)
5 Random Vectors Text Book (Ch. 5)
6 Sum of Random Variables Text Book (Ch. 6)
7 Parameter Estimation Using Sample Mean Text Book (Ch. 7)
8 Hypothesis Testing Text Book (Ch. 8)
9 Estimation of a Random Variable Text Book (Ch. 9)
10 Stochastic Processes Text Book (Ch. 10)
11 Stochastic Processes Text Book (Ch. 10)
12 Random Signal Processing Text Book (Ch. 11)
13 Random Signal Processing Text Book (Ch. 11)
14 Markov Chains Text Book (Ch. 12)
15 Markov Chains Text Book (Ch. 12)
16 Review of the Semester  
Course Notes/Textbooks - Roy D. Yates, David J. Goodman, “Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers”, Wiley, 3rd edition, 2014, ISBN-10: 1107039754, ISBN-13: 978-1107039759
Suggested Readings/Materials - James L. Melsa, Andrew P. Sage, An Introduction to Probability and Stochastic Processes, Dover Books, 2nd Edition, 2013, ISBN-10: 0486490998, ISBN-13: 978-0486490991 Related Research Papers

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
6
30
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm
1
30
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
7
70
Weighting of End-of-Semester Activities on the Final Grade
1
30
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
Study Hours Out of Class
15
4
60
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
5
11
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms
1
20
Final Exams
1
32
    Total
215

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1 Accesses information in breadth and depth by conducting scientific research in Electrical and Electronics Engineering; evaluates, interprets and applies information X
2 Is well-informed about contemporary techniques and methods used in Electrical and Electronics Engineering and their limitations
3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data; can combine and use information from different disciplines
4 Is informed about new and upcoming applications in the field and learns them whenever necessary.

5 Defines and formulates problems related to Electrical and Electronics Engineering, develops methods to solve them and uses progressive methods in solutions.
6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.
7 Designs and implements studies based on theory, experiments and modeling; analyses and resolves the complex problems that arise in this process.
8 Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations; can work independently and takes responsibility.
9  Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.
10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
11 Is knowledgeable about the social, environmental, health, security and law implications of Electrical and Electronics Engineering applications, knows their project management and business applications, and is aware of their limitations in Electrical and Electronics Engineering applications.
12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity. Adheres to the principles of research and publication ethics.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest