Dokuz Eylül University Information Package / Courses Catalog

Description of Individual Course Units

Course Unit Code	Course Unit Title	Type Of Course	D	U	L	ECTS
BIL 3103	DIGITAL SIGNAL PROCESSING	ELECTIVE	3	0	0	5

Offered By

Computer Science

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR ALPER VAHAPLAR

Offered to

Computer Science

Course Objective

In this course, the nature of information, signals, analogue to digital and digital to analog conversion, data storage of audio and video signals, data transformations and applications are introduced.

Learning Outcomes of the Course Unit

1	Have a good understanding of handling of signal data.
2	Have a good understanding of the theory of signal analysis.
3	Have a good ability to apply for noise reduction, noise control (sound signals) and compression-related experiments.
4	Have ability to make use of the algorithmic solution techniques.
5	Have a good understanding of a computer-based solution techniques.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week	Subject	Description
1	Introduction to signal processing
2	Wavelet processing
3	Approximation, coding and compression
4	Simple denoising methods
5	Simple denoising methods
6	Advanced denoising methods
7	Audio processing
8	Midterm exam
9	Higher dimensional signal processing
10	Numerical analysis
11	Optimization
12	Image processing
13	Image processing
14	General review

Recomended or Required Reading

Textbook(s): Weeks, M., Digital Signal Processing Using MATLAB and Wavelets, Infinity Science Press, 2006.
Supplementary Book(s): Hayes, M. H., Statistical Digital Signal Processing, Wiley, 1996.
Proakis, J. G., Manolakis, D.K., Digital Signal Processing: Principles, Algorithms and Applications (3rd Edition) , Prentice Hall; 1995.

Planned Learning Activities and Teaching Methods

The course is taught in a lecture, class presentation and discussion format. Besides the taught lecture, group presentations are to be prepared by the groups assigned and presented in a discussion session. In some weeks of the course, results of the homework given previously are discussed.

Assessment Methods

SORTING NUMBER	SHORT CODE	LONG CODE	FORMULA
1	MTE	MIDTERM EXAM
2	FIN	FINAL EXAM
3	FCG	FINAL COURSE GRADE	MTE * 0.40 + FIN * 0.60
4	RST	RESIT
5	FCGR	FINAL COURSE GRADE (RESIT)	MTE * 0.40 + FIN * 0.60

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

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

cagin.kandemir@deu.edu.tr
ovgu.tekin@deu.edu.tr

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities	Number	Time (hours)	Total Work Load (hours)
Lectures	13	3	39
Preparation before/after weekly lectures	12	3	36
Preparation for Mid-term Exam	1	10	10
Preparation for Final Exam	1	30	30
Preparation for Quiz etc.	2	1	2
In-class practices	4	2	8
Final	1	2	2
Mid-term	1	2	2
Quiz etc.	2	0,5	2
TOTAL WORKLOAD (hours)			131

Contribution of Learning Outcomes to Programme Outcomes

PO/LO	PO.1	PO.2	PO.4	PO.11	PO.13
LO.1	5	4
LO.2	5	4
LO.3	5	4
LO.4			5	4	5
LO.5	5	4	4

COURSE UNIT TITLE

DEGREE PROGRAMMES

Description of Individual Course Units

Offered By

Level of Course Unit

Course Coordinator

Offered to

Course Objective

Learning Outcomes of the Course Unit

Mode of Delivery

Prerequisites and Co-requisites

Recomended Optional Programme Components

Course Contents

Recomended or Required Reading

Planned Learning Activities and Teaching Methods

Assessment Methods

Further Notes About Assessment Methods

Assessment Criteria

Language of Instruction

Course Policies and Rules

Contact Details for the Lecturer(s)

Office Hours

Work Placement(s)

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes

CONTACT INFORMATION