M.SC. in Computer Engineering (Without Thesis)

EEE 601 | Course Introduction and Application Information

Course Name

Fast Filtering Algorithms

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
EEE 601	Fall/Spring	3	0	3	7.5

Prerequisites	None
Course Language	English
Course Type	Elective
Course Level	Third Cycle
Mode of Delivery	-
Teaching Methods and Techniques of the Course	-
National Occupation Classification	-
Course Coordinator	-
Course Lecturer(s)	Doç. Dr. Levent EREN
Assistant(s)	-

Course Objectives

The course aim is to understand the relations between wavelets, filter banks, and multirate systems in area of signal processing and gain the skill in the area of time-frequency analysis of the continuous and discrete signals.

Learning Outcomes

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	Understand the relation between wavelets, filter banks, and multirate systems,
2	Be able to perform time-frequency analysis,
3	Be able to develop fast wavelet algorithms using Matlab,
4	Learn limits of various filters used in different applications..
5	Students will

Course Description

The course will cover fast wavelet transform algorithms – relation to filter banks, wavelet packets construction of wavelets, biorthogonality and biorthogonal basis, biorthogonal system of wavelets - construction, and the lifting scheme.

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

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Related Preparation	Learning Outcome
1	Discrete-time Filters	A Wavelet Tour of Signal Processing, Mallat, Ch. 3
2	Sampling Rate Change Operations	A Wavelet Tour of Signal Processing, Mallat, Ch. 3
3	Filter Banks	A Wavelet Tour of Signal Processing, Mallat, Ch. 7
4	Perfect Reconstruction	A Wavelet Tour of Signal Processing, Mallat, Ch. 7
5	Modulation and Polyphase Representations	A Wavelet Tour of Signal Processing, Mallat, Ch. 7
6	MATLAB® Wavelet Toolbox
7	Orthogonal Filter Banks	A Wavelet Tour of Signal Processing, Mallat, Ch. 7
8	Midterm
9	Maxflat Filters	The course slides
10	Multiresolution Analysis	A Wavelet Tour of Signal Processing, Mallat, Ch. 9
11	Orthogonal Wavelet Bases	The course slides
12	Mallat Pyramid Algorithm	The course slides
13	Accuracy of Wavelet Approximations	The course slides
14	Convergence of the Cascade Algorithm	The course slides
15	Wavelet Compression Algorithms	The course slides
16	Review of the Semester

Course Notes/Textbooks	The textbook referenced above and course
Suggested Readings/Materials	Related Research Papers

EVALUATION SYSTEM

Semester Activities	Number	Weighting	LO 1	LO 2	LO 3	LO 4	LO 5
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	4	20
Presentation / Jury
Project	1	40
Seminar / Workshop
Oral Exams
Midterm	1	40
Final Exam
Total

Weighting of Semester Activities on the Final Grade		60
Weighting of End-of-Semester Activities on the Final Grade		40
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	4	15	60
Presentation / Jury			0
Project	1	35	35
Seminar / Workshop			0
Oral Exam			0
Midterms	1	22	22
Final Exam			0
		Total	225

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 Computer Engineering, evaluates, interprets and applies information.		-	-	-	X	-
2	Is well-informed about contemporary techniques and methods used in Computer 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 Computer 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 modelling, 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 Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications.		X	-	-	-	-
12	Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.		X	-	-	-	-