FACULTY OF ENGINEERING
Department of Mechatronics Engineering
CE 462 | Course Introduction and Application Information
Course Name |
Intoduction to Sparse Representations
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
CE 462
|
Fall/Spring
|
3
|
0
|
3
|
5
|
Prerequisites |
None
|
|||||
Course Language |
English
|
|||||
Course Type |
Service Course
|
|||||
Course Level |
First Cycle
|
|||||
Mode of Delivery | - | |||||
Teaching Methods and Techniques of the Course | Application: Experiment / Laboratory / WorkshopLecture / Presentation | |||||
Course Coordinator | ||||||
Course Lecturer(s) | ||||||
Assistant(s) | - |
Course Objectives | This course seeks a place on solid foundations to introduce the basic theoretical and numerical concepts of sparse representation algorithms, and to illustrate their practical applications. |
Learning Outcomes |
The students who succeeded in this course;
|
Course Description | Provides introductory knowledge on the basics of sparse representations with theoretical and numerical aspects, and practical applications in real life. |
|
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 |
1 | Basic introduction to sparse and redundant representations | |
2 | Underdetermined linear systems, regularization techniques, and convexity | M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, Springer 2010 (Ch. 1) |
3 | Pursuit algorithms in practice | M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, Springer 2010 (Ch. 3) |
4 | From exact to approximate solutions | M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, Springer 2010 (Ch. 5) |
5 | Iterative-shrinkage algorithms | M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, Springer 2010 (Ch. 6) |
6 | Sparsity-seeking methods in signal processing | M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, Springer 2010 (Ch. 9) |
7 | Dictionary learning algorithms | M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, Springer 2010 (Ch. 12) |
8 | MAP and MMSE estimation | M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, Springer 2010 (Ch. 11) |
9 | Applications – Image deblurring, image denoising | M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, Springer 2010 (Ch. 10, Ch.14) |
10 | Applications – Image compression, image super-resolution | M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, Springer 2010 (Ch. 13, Ch.15.4) |
11 | Applications – Image inpainting, image cartoon/texture separation | M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, Springer 2010 (Ch. 15.2, Ch. 15.3) |
12 | Project presentations | |
13 | Project presentations | |
14 | Project presentations | |
15 | Review of the semester | |
16 | Final Exam |
Course Notes/Textbooks | Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, Michael Elad, Springer 2010. ISBN 978-1-4419-7010-7 |
Suggested Readings/Materials |
EVALUATION SYSTEM
Semester Activities | Number | Weigthing |
Participation | ||
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques | ||
Portfolio | ||
Homework / Assignments |
1
|
30
|
Presentation / Jury |
1
|
30
|
Project |
1
|
40
|
Seminar / Workshop | ||
Oral Exams | ||
Midterm | ||
Final Exam | ||
Total |
Weighting of Semester Activities on the Final Grade |
3
|
100
|
Weighting of End-of-Semester Activities on the Final Grade | ||
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 |
14
|
2
|
28
|
Field Work |
0
|
||
Quizzes / Studio Critiques |
0
|
||
Portfolio |
0
|
||
Homework / Assignments |
3
|
5
|
15
|
Presentation / Jury |
1
|
24
|
24
|
Project |
1
|
35
|
35
|
Seminar / Workshop |
0
|
||
Oral Exam |
0
|
||
Midterms |
0
|
||
Final Exam |
0
|
||
Total |
150
|
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
#
|
Program Competencies/Outcomes |
* Contribution Level
|
||||
1
|
2
|
3
|
4
|
5
|
||
1 | To have knowledge in Mathematics, science, physics knowledge based on mathematics; mathematics with multiple variables, differential equations, statistics, optimization and linear algebra; to be able to use theoretical and applied knowledge in complex engineering problems |
|||||
2 | To be able to identify, define, formulate, and solve complex mechatronics engineering problems; to be able to select and apply appropriate analysis and modeling methods for this purpose. |
|||||
3 | To be able to design a complex electromechanical system, process, device or product with sensor, actuator, control, hardware, and software to meet specific requirements under realistic constraints and conditions; to be able to apply modern design methods for this purpose. |
|||||
4 | To be able to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in Mechatronics Engineering applications; to be able to use information technologies effectively. |
|||||
5 | To be able to design, conduct experiments, collect data, analyze and interpret results for investigating Mechatronics Engineering problems. |
|||||
6 | To be able to work effectively in Mechatronics Engineering disciplinary and multidisciplinary teams; to be able to work individually. |
|||||
7 | To be able to communicate effectively in Turkish, both in oral and written forms; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions. |
|||||
8 | To have knowledge about global and social impact of engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of engineering solutions. |
|||||
9 | To be aware of ethical behavior, professional and ethical responsibility; information on standards used in engineering applications. |
|||||
10 | To have knowledge about industrial practices such as project management, risk management and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development. |
|||||
11 | Using a foreign language, he collects information about Mechatronics Engineering and communicates with his colleagues. ("European Language Portfolio Global Scale", Level B1) |
|||||
12 | To be able to use the second foreign language at intermediate level. |
|||||
13 | To recognize the need for lifelong learning; to be able to access information; to be able to follow developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Mechatronics Engineering. |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest