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
Introduction to Systems Analysis EE504 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
None. However, a prior differential equations, signals and systems and/or a circuit theory course is recommended
Course Language English
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 Coordinator
Course Lecturer(s)
  • Prof. Dr. Reşat Özgür Doruk
Course Assistants
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;
  • Explain the general system concepts
  • Distinguish linear and nonlinear systems
  • Describe different linear system representations
  • Model and analyze the systems represented in state space, Laplace and Z domains.
  • Analyze the systems using Fourier analysis approaches.
  • Use linear algebra methods in linear system analyses
  • Interpret the relationships between continuous and discrete time systems.
  • Able to do all the work related to this course in a computational environment such as MATLAB.
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
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.
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
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
Percentage of Final Work 35
Total 100

Course Category

Core Courses X
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
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
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