Syllabus Application
Detection and Estimation Theory
EE 568
Faculty:
Faculty of Engineering and Natural Sciences
Semester:
Fall 2025-2026
Course:
Detection and Estimation Theory - EE 568
Classroom:
FENS-L029,FENS-L030
Level of course:
Masters
Course Credits:
SU Credit:3.000, ECTS:10
Prerequisites:
EE 550 and EE 550
Corequisites:
-
Course Type:
Lecture
Instructor(s) Information
Hüseyin Özkan
- Email: hozkan@sabanciuniv.edu
Course Information
Catalog Course Description
Principle of estimation, detection and time series analysis. Estimation: Linear and nonlinear minimum mean squared error ,estimation and other strategies. Detection: simple, composite, binary and multiple hypotheses, Neyman-Pearson and Bayesian approaches. Time series analysis: Wiener, Kalman filtering , prediction and modal Analysis.
Course Learning Outcomes:
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Course Objective
The goal of this course is to introduce the students to the theory and techniques of modern estimation and detection theory together with time series analysis.
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