| 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;
- Know the statistical decision theory concepts and criteria for the decision.
- Know the basic structure of the transformations and applies them.
- Learn the detection of signal with noises.
- Know the basic models for signal detection.
- Know and applies the methods used for parameter estimation.
- Learn the Wiener and Kalman filters.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | None |
|---|
| Course Description | Detection, estimation and filter theory with applications in Communications and Signal Processing. MAP and MSE detection theories, Wiener filtering. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Detection, estimation and filter theory |
|
2nd Week |
Detection, estimation and filter theory |
|
3rd Week |
Detection, estimation and filter theory |
|
4th Week |
Applications in Communications and Signal Processing |
|
5th Week |
Applications in Communications and Signal Processing |
|
6th Week |
Applications in Communications and Signal Processing |
|
7th Week |
Probability theory |
|
8th Week |
Midterm Exam |
|
9th Week |
Probability theory |
|
10th Week |
MAP and MSE detection theories |
|
11th Week |
MAP and MSE detection theories |
|
12th Week |
MAP and MSE detection theories |
|
13th Week |
Wiener filtering |
|
14th Week |
Wiener filtering |
|
| Recommended or Required Reading | 1. M.D. Srinath, P.K. Rajasekaran, R. Viswanathan, Introduction to statistical signal processing with applications Englewood Cliffs, N.J. Prentice Hall, c1996
2. H. Vincent Poor, An introduction to signal detection and estimation, 2nd Ed., New York. Springer-Verlag, c1994
3. Harry L. Van Trees, Detection, estimation, and modulation theory part 1, New York, Wiley 1968, 2001
|
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Questions/Answers
- Presentation
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
30 |
| Assignment |
2 |
20 |
| Total(%) |
|
50 |
| Contribution of In-term Studies to Overall Grade(%) |
|
50 |
| Contribution of Final Examination to Overall Grade(%) |
|
50 |
| 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 |
|---|
