| Ders Adı | Kodu | Yarıyıl | T+U Saat | Kredi | AKTS |
|---|---|---|---|---|---|
| Kalman Filtering | BSM 604 | 0 | 3 + 0 | 3 | 6 |
| Ön Koşul Dersleri | |
| Önerilen Seçmeli Dersler | |
| Dersin Dili | Türkçe |
| Dersin Seviyesi | Doktora |
| Dersin Türü | Seçmeli |
| Dersin Koordinatörü | Prof.Dr. AHMET ÖZMEN |
| Dersi Verenler | |
| Dersin Yardımcıları | |
| Dersin Kategorisi | Diğer |
| Dersin Amacı | Kalman filters are tools used on many enginnering areas such as communication, signal processing problems, space problems and defense systems etc. Therefore it is valuable for computer engineeringdepartment. |
| Dersin İçeriği | Introduction to Kalman filters, dynamic systems, linear systems and their solutions, discrete linear systems and their solutions. Observability of linear dynamic systems. Applications of kalman filters. |
| # | Ders Öğrenme Çıktıları | Öğretim Yöntemleri | Ölçme Yöntemleri |
|---|---|---|---|
| 1 | Learn Kalman Filtering | Lecture, Question-Answer, Drilland Practice, Self Study, | Testing, Homework, |
| 2 | Learn applicatio of kalman filters in engineering | Lecture, Question-Answer, Drilland Practice, | Testing, Homework, |
| Hafta | Ders Konuları | Ön Hazırlık |
|---|---|---|
| 1 | Introduction to Kalman Filtering, Estimation Methods | |
| 2 | Dynamic Systems, Continuous Lineer Systems and Their Solutions | |
| 3 | Discrete Lineer Systems and their solutions, Observability of Lineer Dynamic System Models, Procedures for Computing Matrix Exponential | |
| 4 | Discovery and Modeling of Random Processes Probability and Random Variables | |
| 5 | Statistical Properties of Random Variables, and Random Process, Lineer Models of Random Processes and Sequences | |
| 6 | Shaping Filters and State Augmentation, Covariance Propagation Equations Orthogonality Princible | |
| 7 | Estimation Problem, Kalman Filter | |
| 8 | Kalman_Bucy Filter, Optimal Linear Predictors Correlated Noise Sources, Relationships between Kalman and Wiener Filters, Quadratic Loss Functions | |
| 9 | Matrix Riccati Differential Equations, Matrix Riccati Equation in Discrete Time | |
| 10 | Relationships between Continuous and Discrete Riccati Equations, Model Equations for Transformed State Variables, Applications of Kalman Filters, Smoothers | |
| 11 | Nonlinear Estimation Problems, Problem Statement Linearization Methods, Linearization about a Nominal Trajectory Linearization about the Estimated Trajectory,Discrete Linearized and Extended Filtering | |
| 12 | Discrete extended Kalman Filter, Continuous Linearized and Extended Filters, Biased Errors in Quadratic Measurements, Application of Nonlinear Filters | |
| 13 | Implementation Methods ,Effect of Roundoff Errors on Kalman Filters | |
| 14 | Earlier Implemantation Methods, Factorization Methods for Kalman Filtering |
| Kaynaklar | |
|---|---|
| Ders Notu | |
| Ders Kaynakları | Kalman Filtering [Theory and Practice]/ Mohinder S.Grawal, Angus P. Andrews, 1993 Probability and Stochastic Processes for Enginers/ Carl W.Helstrom,1984 Introduction to Stochastic Processes/ Paul G.Hoel, Sidney C.Port, Charles J.Stone 1972 Probability, Random Variables and Stochastics Processes/ Athanasios Papoulis , 1991 Lessons in Estimation Theory for Signal Processing , Communications and Control / Jerry M.Mendel, 1995 |
| Sıra | Program Çıktıları | Katkı Düzeyi | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | ability to access wide and deep information with scientific researches in the field of Engineering, evaluate, interpret and implement the knowledge gained in his/her field of study | X | |||||
| 2 | ability to complete and implement “limited or incomplete data” by using the scientific methods. | X | |||||
| 3 | ability to consolidate engineering problems, develop proper method(s) to solve and apply the innovative solutions to them | X | |||||
| 4 | ability to develop new and original ideas and method(s), to develop new innovative solutions at design of system, component or process | X | |||||
| 5 | gain comprehensive information on modern techniques, methods and their borders which are being applied to engineering | X | |||||
| 6 | ability to design and apply analytical, modelling and experimental based research, analyze and interpret the faced complex issues during the design and apply process | X | |||||
| 7 | gain high level ability to define the required information and data | X | |||||
| 8 | ability to work in multi-disciplinary teams and to take responsibility to define approaches for complex situations | X | |||||
| 9 | systematic and clear verbal or written transfer of the process and results of studies at national and international environments | X | |||||
| 10 | aware of social, scientific and ethical values guarding adequacy at all professional activities and at the stage of data collection, interpretation and announcement | X | |||||
| 11 | aware of new and developing application of profession and ability to analyze and study on those applications | X | |||||
| 12 | ability to interpret engineering application’s social and environmental dimensions and it’s compliance with the social environment | X | |||||
| Değerlendirme Sistemi | |
|---|---|
| Yarıyıl Çalışmaları | Katkı Oranı |
| 1. Ara Sınav | 100 |
| Toplam | 100 |
| 1. Yıl İçinin Başarıya | 50 |
| 1. Final | 50 |
| Toplam | 100 |
| AKTS - İş Yükü Etkinlik | Sayı | Süre (Saat) | Toplam İş Yükü (Saat) |
|---|---|---|---|
| Course Duration (Including the exam week: 16x Total course hours) | 16 | 3 | 48 |
| Hours for off-the-classroom study (Pre-study, practice) | 16 | 3 | 48 |
| Mid-terms | 1 | 20 | 20 |
| Final examination | 1 | 25 | 25 |
| Toplam İş Yükü | 141 | ||
| Toplam İş Yükü / 25 (Saat) | 5,64 | ||
| Dersin AKTS Kredisi | 6 | ||