ECTS - Detection and Estimation
Detection and Estimation (EE611) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Detection and Estimation | EE611 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Question and Answer, Drill and Practice. |
| Course Lecturer(s) |
|
| Course Objectives | Understanding detection theory; binary hypothesis testing, M-ary testing, Bayes and Neyman-Pearson detectors, min-max. theory, Understanding estimation theory; linear and nonlinear estimation, parameter estimation, MAP and maximum likelihood estimators, Cramér-Rao bounds, asymptotic properties of estimators, waveform detection and estimation, Wiener filtering and Kalman-Bucy filtering, spectral estimation, and important research topics for Ph.D. work. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Neyman-Pearson detector, hypothesis testing, maximum likelihood estimator, MAP, Kalman filtering, Wiener filtering, detection and estimation performance evaluation. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Course overview and introduction. Introduction to hypothesis testing | |
| 2 | Bayesian hypothesis testing | |
| 3 | Min-max hypothesis testing | |
| 4 | Neyman-Pearson and composite hypothesis testing | |
| 5 | Detection of deterministic signals | |
| 6 | Detection of signals with random parameters and stochastic signals | |
| 7 | Performance evaluation of signal detection procedures | |
| 8 | MIDTERM EXAM | |
| 9 | Introduction to parameter estimation | |
| 10 | Bayesian parameter estimation | |
| 11 | Maximum likelihood estimation | |
| 12 | Signal estimation: Kalman-Bucy filtering | |
| 13 | Wiener filtering | |
| 14 | Performance evaluation of estimation procedures | |
| 15 | Selected applications (reviewing research papers) | |
| 16 | Selected applications (reviewing research papers) |
Sources
| Course Book | 1. Detection, Estimation and Modulation Theory Part I: Detection, Estimation and Filtering Theory, 2nd Edition Harry L. Van Trees,Kristine L. Bell, Zhi Tian, 2013. |
|---|---|
| 2. H. V. Poor, "An Introduction to Signal Detection and Estimation", Springer, 2/e, 1998. | |
| 3. • S. M. Kay, "Fundamentals of Statistical Signal Processing: Estimation Theory", Prentice Hall PTR, 1993. | |
| 4. • S. M. Kay, "Fundamentals of Statistical Signal Processing: Detection Theory", Prentice Hall PTR, 1998. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | 5 | 25 |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 35 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 7 | 100 |
| Percentage of Semester Work | |
|---|---|
| Percentage of Final Work | 100 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Ability to apply knowledge on Mathematics, Science and Engineering to advanced systems. | X | ||||
| 2 | Implementing long-term research and development studies in major areas of Electrical and Electronics Engineering. | X | ||||
| 3 | Ability to use modern engineering tools, techniques and facilities in design and other engineering applications. | X | ||||
| 4 | Graduating researchers active on innovation and entrepreneurship. | |||||
| 5 | Ability to report and present research results effectively. | |||||
| 6 | Increasing the performance on accessing information resources and on following recent developments in science and technology. | |||||
| 7 | An understanding of professional and ethical responsibility. | |||||
| 8 | Increasing the performance on effective communications in both Turkish and English. | |||||
| 9 | Increasing the performance on project management. | |||||
| 10 | Ability to work successfully at project teams in interdisciplinary fields. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 5 | 80 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | 5 | 6 | 30 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 4 | 4 |
| Prepration of Final Exams/Final Jury | 1 | 5 | 5 |
| Total Workload | 167 | ||