ECTS - Introduction to Systems Analysis
Introduction to Systems Analysis (EE504) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Introduction to Systems Analysis | EE504 | Area Elective | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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None. However, a prior differential equations, signals and systems and/or a circuit theory course is recommended |
Course Language | English |
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Course Type | Elective Courses |
Course Level | Natural & Applied Sciences Master's Degree |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture, Discussion, Question and Answer, Problem Solving. |
Course Lecturer(s) |
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Course Objectives | Teaching the graduate students of basic concepts such as basic linear algebra, linear system representations, analysis in Laplace, Z, Fourier and State-Space domains, transformation between continuous and discrete time systems. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Review of linear algebra concepts, classifications of systems and system representations, continuous and discrete time systems, state space realizations, analysis techniques: frequency domain, Laplace and z-domain analyses, solutions of linear systems, stability analysis; assessment of the techniques by a computational tool such as MATLAB. |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Elementary matrix theory, Matrix addition and multiplication, Matrix and Vector multiplication, Properties of linear equations | Review last week and Glance this week’s topics from the lecture |
2 | Vectors, Vector spaces, Linear dependence and independence, Basis concept, Linear spans, Normed vector spaces | Glance this week’s topics from the lecture |
3 | Null and Range spaces of matrices, Eigenvalues, Eigenvectors, Diagonalization | Review last week and Glance this week’s topics from the lecture |
4 | Singular Value Decomposition | Glance the last weeks topics |
5 | MATLAB Session: Vectors and Matrices in MATLAB | Review last week and Glance this week’s topics from the lecture |
6 | Introduction to Fourier, Laplace and Z-Transforms | Review last week and Glance this week’s topics from the lecture |
7 | Continuous and Discrete Time systems, Transfer function representations | Review last week and Glance this week’s topics from the lecture |
8 | MIDTERM-I (1 Hour MATLAB Exam+2 Hour Theoretical) | Review last week and Glance this week’s topics from the lecture |
9 | Representation of linear systems in state space and transformation between transfer function and state space representations. | Review last week and Glance this week’s topics from the lecture |
10 | Solutions of linear systems | Review last week and Glance this week’s topics from the lecture |
11 | Analysis in Fourier Domain (Frequency response) | Review last week and Glance this week’s topics from the lecture |
12 | Analysis in Fourier Domain (Frequency response) | Review last week and Glance this week’s topics from the lecture |
13 | Connections to nonlinear systems, linearization and local stability | Review last week and Glance this week’s topics from the lecture |
14 | Transformation between continuous and discrete time systems (s-to-z) | Review last week and Glance this week’s topics from the lecture |
15 | The transformation between continuous and discrete time systems in state space. | Review the last week's topics |
16 | MIDTERM-II (1 Hour MATLAB Exam+2 Hour Theoretical) | Review last week and Glance this week’s topics from the lecture |
Sources
Course Book | 1. Oppenheim, A. V., & Willsky, A. S. (1997). with SH Nawab, Signals and Systems. Prentice—Hall,, 1, 997. |
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2. Ogata, K. (1997). Modern Control Engineering (3rd Ed.). Prentice-Hall, Inc., Upper Saddle River, NJ, USA. | |
3. Ogata, K. (1995). Discrete-time control systems (Vol. 2). Englewood Cliffs, NJ: Prentice Hall. | |
4. Kuo, B. C. (1981). Automatic control systems. (8th ed.). John Wiley & Sons, Inc., New York, NY, USA. | |
5. Lipschutz, S., & Lipson, M. (2000). Schaum's Outline of Linear Algebra. McGraw Hill Professional. | |
Other Sources | 6. Notes to be distributed by the instructor(s) of the course in class. |
Evaluation System
Requirements | Number | Percentage of Grade |
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Attendance/Participation | - | - |
Laboratory | - | - |
Application | - | - |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | - | - |
Presentation | - | - |
Project | - | - |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 2 | 50 |
Final Exam/Final Jury | 1 | 35 |
Toplam | 3 | 85 |
Percentage of Semester Work | 65 |
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Percentage of Final Work | 35 |
Total | 100 |
Course Category
Core Courses | X |
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Major Area Courses | |
Supportive Courses | |
Media and Managment Skills Courses | |
Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
# | Program Qualifications / Competencies | Level of Contribution | ||||
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1 | 2 | 3 | 4 | 5 | ||
1 | Ability to carry out advanced research activities, both individual and as a member of a team | |||||
2 | Ability to evaluate research topics and comment with scientific reasoning | |||||
3 | Ability to initiate and create new methodologies, implement them on novel research areas and topics | |||||
4 | Ability to produce experimental and/or analytical data in systematic manner, discuss and evaluate data to lead scintific conclusions | |||||
5 | Ability to apply scientific philosophy on analysis, modelling and design of engineering systems | |||||
6 | Ability to synthesis available knowledge on his/her domain to initiate, to carry, complete and present novel research at international level | |||||
7 | Contribute scientific and technological advancements on engineering domain of his/her interest area | |||||
8 | Contribute industrial and scientific advancements to improve the society through research activities |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
Laboratory | |||
Application | |||
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | 14 | 3 | 42 |
Presentation/Seminar Prepration | |||
Project | |||
Report | |||
Homework Assignments | |||
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 2 | 10 | 20 |
Prepration of Final Exams/Final Jury | 1 | 20 | 20 |
Total Workload | 130 |