COURSE UNIT TITLE

: ADVANCED DIGITAL SIGNAL PROCESSING

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EEE 5066 ADVANCED DIGITAL 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 DAMLA GÜRKAN KUNTALP

Offered to

GEOGRAPHICAL INFORMATION SYSTEMS (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)

Course Objective

Learning Outcomes of the Course Unit

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Framework for Digital Filter Design
2 Linear prediction
3 Linear prediction cont.
4 Spectral estimation; frequency resolution, non-parametric methods, periodogram, Barlett method, Welch method
5 Spectral estimation; parametric method, AR, MA and ARMA models
6 Adaptive filtering; Wiener filtering
7 Adaptive filtering; LMS, RLS algorithms
8 Midterm
9 Multirate digital signal processing; decimators and interpolators design and implementation
10 Multirate digital signal processing; multistage sampling rate conversion
11 : Multirate digital signal processing; perfect reconstruction filter bank, quadratic mirror filter bank and its design
12 Finite wordlength effect
13 Cepstrum analysis and homomorphic deconvolution*
14 Cepstrum analysis and homomorphic deconvolution cont.*

Recomended or Required Reading

Text book: J. G. Proakis, et. al. "Digital Signal Processing", Pearson, 2007.
References:
Digital Signal Processing, Ludeman, S.K: Mitra, McGraw-Hill, 2001.
Discrete-Time Signal Processing, Alan V. Oppenheim, Ronald W.Schaffer, Prentice and Hall, 1989.

Planned Learning Activities and Teaching Methods

Theoretical contenet is provided in the lectures. To reinforce and extend understanding of topics that are covered theoretically in lectures, projects and homeworks are assigned as applications.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MD Midterm
2 PR Proje
3 HW Homework
4 QZ Quiz
5 BNS BNS MD* 0.30 + PR * 0.30 + HW * 0.20 + QZ * 0.20


Further Notes About Assessment Methods

None

Assessment Criteria

Learning outcomes will be evaluated by homework problems, and exams. Application of theoretical concepts to practical problems will be evaluated through assigned projects.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

damla.kuntalp@deu.edu.tr

Electrical and Electronics Engineering Department
Office Phone #: 301 7166

Office Hours

To be announced at the beginning of the semester.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparation for midterm exam 1 20 20
Preparation for quiz etc. 6 2 12
Preparations before/after weekly lectures 13 3 39
Design Project 1 40 40
Preparing assignments 3 10 30
Midterm 1 3 3
Quiz etc. 6 1 6
TOTAL WORKLOAD (hours) 189

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15