| Course Type | Elective Course |
|---|
| Course Level | Master's Degree With Thesis |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 10 |
|---|
| Name of Lecturer(s) |
- |
| Learning Outcomes |
At the end of this course, the students;
- Gain an ability to solve problems.
- Know the basic transformations and use them.
- Know and apply the probability theory.
- Wil be able to calculate density and distribution functions.
- Know and use random process applications.
- Know and improve the power spectrum estimation methods.
- Able to perform analysis of random processes.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | None |
|---|
| Course Description | Random Processes is a graduate-level course based on probability theory given at the undergraduate level and in which random (stochastic) processes are explained. The course covers the basic concepts of random processes in detail. In addition, applications/examples in the fields of communication, signal processing, control systems and computer science are examined. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Review of Probability Theory |
|
2nd Week |
Random Variables |
|
3rd Week |
Random Variables |
|
4th Week |
Multiple Random Variables |
|
5th Week |
Multiple Random Variables |
|
6th Week |
Random Variable Functions, |
|
7th Week |
Random Variable Functions, |
|
8th Week |
Midterm |
|
9th Week |
Estimation and Limit Theorems |
|
10th Week |
Random Processes |
|
11th Week |
Random Processes |
|
12th Week |
Analysis and Processing of Random Processes, (Markov, Poisson, Wiener Processes) |
|
13th Week |
Analysis and Processing of Random Processes, (Markov, Poisson, Wiener Processes) |
|
| Recommended or Required Reading | 1. Fundamentals of Applied Probability and Random Processes. 2nd Edition, O.C. Ibe; Elsevier Academic Press.
2. Probability and Stochastic Processes. R.D.Yates, D.J.Goodman; 3rd Edition; Wiley. |
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Questions/Answers
- Problem Solving
- Practice
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
35 |
| Assignment |
1 |
20 |
| Total(%) |
|
55 |
| Contribution of In-term Studies to Overall Grade(%) |
|
55 |
| Contribution of Final Examination to Overall Grade(%) |
|
45 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
3 |
3 |
| Preparation for Quiz |
0 |
0 |
0 |
| Individual or group work |
14 |
8 |
112 |
| Preparation for Final exam |
1 |
40 |
40 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
30 |
30 |
| Laboratory (including preparation) |
0 |
0 |
0 |
| Final exam |
1 |
3 |
3 |
| Homework |
2 |
35 |
70 |
| Total Work Load | 300 |
| Total Work Load / 30 (h) | 10 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
