| TYPE OF COURSE UNIT | Elective Course |
| LEVEL OF COURSE UNIT | Master's Degree With Thesis |
| YEAR OF STUDY | - |
| SEMESTER | - |
| NUMBER OF ECTS CREDITS ALLOCATED | 10 |
| NAME OF LECTURER(S) | Associate Professor Selda Güney
|
| LEARNING OUTCOMES OF THE COURSE UNIT |
At the end of this course, the students;
1) Know the statistical decision theory concepts and criteria for the decision.
2) Know the basic structure of the transformations and applies them.
3) Learn the detection of signal with noises.
4) Know the basic models for signal detection.
5) Know and apply the methods used for parameter estimation.
6) Learn the Wiener and Kalman filters.
|
| MODE OF DELIVERY | Face to face |
| PRE-REQUISITES OF THE COURSE | No |
| RECOMMENDED OPTIONAL PROGRAMME COMPONENT | |
| COURSE DEFINITION | |
| COURSE CONTENTS |
|
| RECOMENDED OR REQUIRED READING | |
| PLANNED LEARNING ACTIVITIES AND TEACHING METHODS | Lecture,Presentation,Problem Solving |
| 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 WORKLOAD |
| Activities |
Number |
Hours |
Workload |
| Midterm exam | 1 | 2 | 2 | | Preparation for Quiz | | | | | Individual or group work | 14 | 9 | 126 | | Preparation for Final exam | 1 | 50 | 50 | | Course hours | 14 | 3 | 42 | | Preparation for Midterm exam | 1 | 25 | 25 | | Laboratory (including preparation) | | | | | Final exam | 1 | 2 | 2 | | Homework | 1 | 40 | 40 | | Total Workload | | | 287 |
|---|
| Total Workload / 30 | | | 9,56 |
|---|
| ECTS Credits of the Course | | | 10 |
|---|
|
| LANGUAGE OF INSTRUCTION | Turkish |
| WORK PLACEMENT(S) | No |
| | |
