COURSE UNIT TITLE

: MODERN SPECTRAL ESTIMATION

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EEE 5103 MODERN SPECTRAL ESTIMATION 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

ASSISTANT PROFESSOR KADRIYE FILIZ BALBAL

Offered to

ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING NON -THESIS (EVENING PROGRAM) (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)

Course Objective

The goal of this course is to introduce the students into various spectral estimation techniques which try to determine the spectral content of a random process based on a finite set of observations and to equip the students with the abilities of simulating various spectral estimation techniques on computer using MATLAB programming language.

Learning Outcomes of the Course Unit

1   To be able to describe the problem of spectral estimation.
2   To be able to explain different spectral estimation methods using examples.
3   To be able to develop alternative spectral estimation solutions for a data set.
4   To be able to compare classical and modern spectral estimation methods by emphasizing their differences.
5   To be able to propose a suitable spectral estimation method for a specific problem.
6   To be able to compose computer programs for simulating various spectral estimation methods via MATLAB programming language.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

EEE 5129 - Random Variables and Stochastic Processes
EEE 5087 - Statistical Estimation Theory in Signal Processing

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction
2 Periodogram
3 Blackman-Tukey Spectral Estimation
4 Parametric Modeling
5 Model Fitting
6 Properties of AR Processes
7 Estimation of AR Parameters and Reflection Coefficients
8 AR Spectral Estimation Methods
9 Model Order Selection
10 MA Spectral Estimation
11 ARMA Spectral Estimation
12 ARMA Spectral Estimation Methods
13 Least Squares Modified Yule-Walker Equations
14 Minimum Variance Spectral Estimation

Recomended or Required Reading

Ana kaynak: Modern Spectral Estimation:Theory and Application, S. M. Kay, Prentice Hall, 1988.
Yardımcı kaynaklar: Introduction to Spectral Analysis, P. Stoica and R. Moses, Prentice Hall, 1997.
Diğer ders materyalleri: Course notes.

Planned Learning Activities and Teaching Methods

Lectures+Homeworks+Data Project+Term Project

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 PRJ PROJECT
3 FINAP PROJECT
4 FCG FINAL COURSE GRADE ASG * 0.20 + PRJ *0.35 + FINAP * 0.45


Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

olcay.akay@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Design Project 2 25 50
Preparing presentations 1 10 10
Preparations before/after weekly lectures 14 4 56
Preparing assignments 10 4 40
TOTAL WORKLOAD (hours) 198

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.1121
LO.21121111
LO.324411112
LO.421
LO.521253121211
LO.611225

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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