M.SC. in Electrical and Electronics Engineering (With Thesis)

EEE 509 | Course Introduction and Application Information

Course Name

Selected Topics in Signal Processing

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
EEE 509	Fall/Spring	3	0	3	7.5

Prerequisites	None
Course Language	English
Course Type	Elective
Course Level	Second Cycle
Mode of Delivery	-
Teaching Methods and Techniques of the Course	-
National Occupation Classification	-
Course Coordinator	Prof. Dr. Aydın AKAN
Course Lecturer(s)	Prof. Dr. Aydın AKAN
Assistant(s)	-

Course Objectives

This course covers the fundamentals of discrete-time signals and systems, design and implementation of signal processing systems, and selected topics from the current state-of-the-art research and developments in signal processing.

Learning Outcomes

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	learn how to use time-domain and transform-domain techniques for representing and analyzing discrete-time signals and systems,
2	know how to use discrete-time systems to process continuous-time signals,
3	know how to design and implement discrete-time filters,
4	know how to design optimal filters for estimating discrete-time random processes,
5	know how to develop adaptive filters capable of responding to varying processing requirements,
6	know how to design and implement various signal processing algorithms using Matlab and signal processing toolbox.

Course Description

Techniques used in the time-frequency analysis of nonstationary signals: Empirical Time Decomposition, Ensemble Empirical Time Decomposition, Multivariate Emprirical Time Decomposition, Variational Mode Decomposition, Intrinsic Time-Scale Decomposition, Short-time Fourier Transform, Fourier Based Synchrosqueezing Transform

Course Category	Core Courses
	Major Area Courses	X
	Supportive Courses
	Media and Management Skills Courses
	Transferable Skill Courses

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Related Preparation	Learning Outcome
1	Empirical Mode Decomposition	Related research papers
2	Ensemble Empirical Mode Decomposition	Related research papers
3	Multivariate Empirical Mode Decomposition	Related research papers
4	Variational Mode Decomposition	Related research papers
5	Multivariate Variational Mode Decomposition	Related research papers
6	Intrinsic Time-Scale Decomposition	Related research papers
7	Intrinsic Time-Scale Decomposition Applications	Related research papers
8	Short-time Fourier Transform	Related research papers
9	Fourier Based Synchrosqueezing Transform (FSST)	Related research papers
10	Studen presentations	Related research papers
11	Student presentations	Related research papers
12	Student presentations	Related research papers
13	Student presentations	Related research papers
14	Student presentations	Related research papers
15	Student presentations	Related research papers
16	Review of the semester

Course Notes/Textbooks

1) Time-Frequency Signal Analysis and Processing, 2nd Edition, Editor: Boualem Boashash, Academic Press, ISBN: 9780123984999, Jan. 2016.

2) Time-Frequency Analysis, Leon Cohen, Prentice Hall, 1995. ISBN 0-13-594532-1

The textbook referenced above and course slides

Suggested Readings/Materials

Related Research Papers

EVALUATION SYSTEM

Semester Activities	Number	Weighting	LO 1	LO 2	LO 3	LO 4	LO 5	LO 6
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	1	20
Presentation / Jury	1	20
Project	1	30
Seminar / Workshop
Oral Exams
Midterm
Final Exam	1	30
Total

Weighting of Semester Activities on the Final Grade	3	70
Weighting of End-of-Semester Activities on the Final Grade	1	30
Total

ECTS / WORKLOAD TABLE

Semester Activities	Number	Duration (Hours)	Workload
Theoretical Course Hours (Including exam week: 16 x total hours)	16	3	48
Laboratory / Application Hours (Including exam week: '.16.' x total hours)	16		0
Study Hours Out of Class	15	4	60
Field Work			0
Quizzes / Studio Critiques			0
Portfolio			0
Homework / Assignments	1	47	47
Presentation / Jury	1	20	20
Project	1	40	40
Seminar / Workshop			0
Oral Exam			0
Midterms			0
Final Exam	1		0
		Total	215

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	Accesses information in breadth and depth by conducting scientific research in Electrical and Electronics Engineering; evaluates, interprets and applies information		-	X	-	-	-
2	Is well-informed about contemporary techniques and methods used in Electrical and Electronics Engineering and their limitations		-	-	-	X	-
3	Uses scientific methods to complete and apply information from uncertain, limited or incomplete data; can combine and use information from different disciplines		-	-	X	-	-
4	Is informed about new and upcoming applications in the field and learns them whenever necessary.		-	-	X	-	-
5	Defines and formulates problems related to Electrical and Electronics Engineering, develops methods to solve them and uses progressive methods in solutions.		-	-	-	-	X
6	Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.		-	-	X	-	-
7	Designs and implements studies based on theory, experiments and modeling; analyses and resolves the complex problems that arise in this process.		-	-	-	-	X
8	Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations; can work independently and takes responsibility.		-	-	X	-	-
9	Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.		-	-	X	-	-
10	Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.		X	-	-	-	-
11	Is knowledgeable about the social, environmental, health, security and law implications of Electrical and Electronics Engineering applications, knows their project management and business applications, and is aware of their limitations in Electrical and Electronics Engineering applications.		X	-	-	-	-
12	Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity. Adheres to the principles of research and publication ethics.		X	-	-	-	-