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 | Ph.D. |
| 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 | Is independently able to build a problem in the area of study, solve the problem by developing solution techniques and assess the solutions. | X | ||||
| 2 | Is capable of creating a groundwork in the fundamental branches of mathematics as well as in his/her research area | X | ||||
| 3 | follows the latest national and international literature in Mathematics and in his/her area of research; and uses them in his/her related studies | X | ||||
| 4 | observes and adopts the scientific ethical values in his/her professional and social life | X | ||||
| 5 | presents in Turkish and English in academic/scientific events the results of his/her research or the latest studies and findings on a special topic and participates in discussions | X | ||||
| 6 | Develops skills to work independently or as a member of a team | X | ||||
| 7 | Develops competences in the areas of creative and critical thinking, problem solving and producing original studies. Follows recent scientific studies, is capable of making an analysis, synthesis and assessment of the knowledge acquired | X | ||||
| 8 | Is open to lifelong improvement of his/her acquired knowledge, skills and competences. | X | ||||
| 9 | Is able to apply the acquired knowledge and problem-solving skills to interdisciplinary studies, proposes different solution methods to problems in terms of mathematical models and from a mathematical point of view | X | ||||
| 10 | Uses the mathematical based softwares, informatics and communication technologies for scientific purposes | X | ||||
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 | ||