COURSE UNIT TITLE

: STATISTICAL DETECTION THEORY IN SIGNAL PROCESSING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EEE 5084 STATISTICAL DETECTION THEORY IN SIGNAL PROCESSING ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR MEHMET EMRE ÇEK

Offered to

ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)

Course Objective

The goal of this course is to introduce the students into statistical detection theory methods which are fundamentally important in designing electronic signal processing systems for decision making and information extraction, and to equip the students with the abilities of developing various detection algorithms on computer using MATLAB programming language.

Learning Outcomes of the Course Unit

1   To be able to define the concept of statistical decision making.
2   To be able to differentiate detection methods for deterministic and random signals.
3   To be able to explain Neyman-Pearson and Bayes detection philosophies.
4   To be able to compose MATLAB computer programs for realizing detection algorithms on computer.
5   To be able to propose alternative detection methods for solving a statistical detection problem.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction
2 Statistical Decision Theory
3 Statistical Decision Theory
4 Neyman-Pearson Lemma
5 Minimum Bayes Risk Detector
6 Detection of Known (Deterministic) Signals
7 Detection of Known (Deterministic) Signals
8 Detection of Random Signals
9 Detection of Random Signals
10 GLRT Test
11 Rao Test
12 Nongaussian Noise
13 Model Change Detection
14 Extension for Complex Data

Recomended or Required Reading

Textbook: Fundamentals of Statistical Signal Processing: Detection Theory, S. Kay, Prentice Hall, 1998.
Supplementary Book: Statistical Signal Processing Detection, Estimation and Time Series Analysis, L. L. Scharf, Addison Wesley, 1991.
Other materials: Course notes.

Planned Learning Activities and Teaching Methods

Presentations + Term Project

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 PRS PRESENTATION
2 ASG ASSIGNMENT
3 FCG FINAL COURSE GRADE PRS * 0.50 + ASG * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Homeworks, Term Project

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

emre.cek@deu.edu.tr

Office Hours

Office Hours will be announced at the beginning of the term.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 2 28
Preparing assignments 1 20 20
Preparing presentations 14 5 70
Design Project 1 20 20
Reading 10 2 20
Project Assignment 1 3 3
TOTAL WORKLOAD (hours) 203

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.134432221
LO.243342221
LO.3224111212
LO.4122115
LO.51254421

CONTACT INFORMATION
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