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| ELK5700 | System Identificaion and Estimation Methods | 3+0+0 | ECTS:7.5 | | Year / Semester | Spring Semester | | Level of Course | Second Cycle | | Status | Elective | | Department | DEPARTMENT of ELECTRICAL and ELECTRONICS ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | -- | | Co-Lecturer | None | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The aim of this course is to provide informatipon mathematical fundamentals of parameter estimation and identification of systems. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | explain difference between linear and nonlinear parameter estimation. | 1,3 | 1,2 | | PO - 2 : | describe beahiours of estimation methods. | 1,2,5 | 1,2 | | PO - 3 : | simulate estimation methods on MATLAB. | 1,5,6 | 1,2 | | PO - 4 : | provide information on system identification | 1,3,4,5 | 1,2 | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | | |
| Presentation of basic ideas and concepts, Basic properties of signals, Brief introduction of systems, Random variables, Stochastic processes, Identification and modeling, Criteria for model selection, Statistical properites of estimates, Linear estimation technique, Linearization, Iterative nonlinear estimation techniques, Gradient method, Newton method, Newton-Gauss method, Marquardt-Levenberg method
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Presentation of basic ideas and concepts | | | Week 2 | Basic properties of signals | | | Week 3 | Brief introduction of systems | | | Week 4 | Random variables, Stochastic processes | | | Week 5 | Identification and modeling | | | Week 6 | Criteria for model selection | | | Week 7 | Statistical properites of estimates | | | Week 8 | Linear estimation technique | | | Week 9 | Midterm exam | | | Week 10 | Linearization | | | Week 11 | Iterative nonlinear estimation techniques | | | Week 12 | Gradient method | | | Week 13 | Newton method, Newton-Gauss method | | | Week 14 | Marquardt-Levenberg method | | | Week 15 | Project presentation | | | Week 16 | End-of-term exam | | | |
| 1 | Bard Y., 1974; Nonlinear Parameter Estimation, Academic Press, Newyork and London | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | | 2,00 | 30 | | Project | 15 | | 1,00 | 20 | | End-of-term exam | 16 | | 1,50 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 13 | 39 | | Sınıf dışı çalışma | 4 | 13 | 52 | | Laboratuar çalışması | 0 | 0 | 0 | | Arasınav için hazırlık | 3 | 6 | 18 | | Arasınav | 2 | 1 | 2 | | Uygulama | 0 | 0 | 0 | | Klinik Uygulama | 0 | 0 | 0 | | Ödev | 0 | 0 | 0 | | Proje | 6 | 13 | 78 | | Kısa sınav | 0 | 0 | 0 | | Dönem sonu sınavı için hazırlık | 3 | 6 | 18 | | Dönem sonu sınavı | 2 | 1 | 2 | | Diğer 1 | 0 | 0 | 0 | | Diğer 2 | 0 | 0 | 0 | | Total work load | | | 209 |
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