Akademik Dersler - Tanıtım


Code - Course Title	EEM547 - Fundamentals of Detection and Estimation
Course Type	Required Courses
Language of Instruction	İngilizce
Laboratory + Practice	3+0
ECTS	7.5
Course Instructor(s)
Mode of Delivery	Mode of delivery of this course is face-to-face instruction, including projects.
Prerequisites	There is no prerequisite or co-requisite for this course.
Courses Recomended	Digital signal processing, probability and random processes, linear algebra.
Required or Recommended Resources	Course webpage.
Recommended Reading List	The Internet-based resources.
Assessment methods and criteria	2 midterms, 1 final, 1 project
Work Placement	Project.
Sustainability Development Goals

Weeks	Topics
Week - 1	Introduction to signal detection and estimation
Week - 2	Review of the theory of random variables and random signals
Week - 3	Classical estimation theory, general minimum variance unbiased estimation
Week - 4	Cramer-Rao Lower Bound
Week - 5	Cramer-Rao Lower Bound
Week - 6	Linear models and best linear unbiased estimators
Week - 7	Maximum likelihood estimation
Week - 8	Least squares estimation
Week - 9	Bayesian estimation
Week - 10	Wiener and Kalman filtering
Week - 11	Wiener and Kalman filtering
Week - 12	Classical detection theory
Week - 13	Classical detection theory
Week - 14	Detection in Gaussian and nonGaussian noise

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
Toplam (%)		0