Akademik Dersler - Tanıtım


Code - Course Title	EEM643 - Estimation Theory
Course Type	Elective Courses
Language of Instruction	İngilizce
Laboratory + Practice	3+0
ECTS	7.5
Course Instructor(s)	DOKTOR ÖĞRETİM ÜYESİ ALTAN ONAT
Mode of Delivery	Face to Face
Prerequisites	None.
Courses Recomended	None.
Required or Recommended Resources	T. Kailath A. H. Sayed and B. Hassibi, Linear Estimation, Prentice Hall Informationand Systems Sciences Series, Prentice Hall, New Jersey, 2000
Recommended Reading List	All textbooks covering linear estimation.
Assessment methods and criteria	Two midterm exams and one final exam
Work Placement	None.
Sustainability Development Goals

Weeks	Topics
Week - 1	Review of fundamental concepts (Signals and Systems, Linear State Space Models, Random Processes etc.)
Week - 2	Review of fundamental concepts (Signals and Systems, Linear State Space Models, Random Processes etc.)
Week - 3	Deterministic Least Squares Problems
Week - 4	Deterministic Least Squares Problems
Week - 5	Stochastic Least Squares Problems
Week - 6	Stochastic Least Squares Problems
Week - 7	The Innovation Process
Week - 8	The Innovation Process
Week - 9	Wiener Theory for Scalar Processes
Week - 10	Wiener Theory for Scalar Processes
Week - 11	Linear Kalman Filter
Week - 12	Linear Kalman Filter
Week - 13	Extended Kalman Filter
Week - 14	Extended Kalman Filter

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
1.Midterm Exam	1	30
Project	1	30
Final Exam	1	40
Toplam (%)		100