# 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 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 N/A Natural & Applied Sciences Master's Degree Face To Face Lecture, Discussion, Question and Answer, Problem Solving. Prof. Dr. Reşat Özgür Doruk 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. 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. 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. 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 35 100

### Course Category

Core Courses X

### The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Ability to expand and get in-depth information with scientific researches in the field of mechanical engineering, evaluate information, review and implement.
2 Have comprehensive knowledge about current techniques and methods and their limitations in Mechanical engineering.
3 To complete and apply knowledge by using scientific methods using uncertain, limited or incomplete data; use information from different disciplines.
4 Being aware of the new and developing practices of Mechanical Engineering and being able to examine and learn when needed.
5 Ability to define and formulate problems related to Mechanical Engineering and develop methods for solving and apply innovative methods in solutions.
6 Ability to develop new and/or original ideas and methods; design complex systems or processes and develop innovative/alternative solutions in the designs.
7 Ability to design and apply theoretical, experimental and modeling based researches; analyze and solve complex problems encountered in this process.
8 Work effectively in disciplinary and multi-disciplinary teams, lead leadership in such teams and develop solution approaches in complex situations; work independently and take responsibility.
9 To establish oral and written communication by using a foreign language at least at the level of European Language Portfolio B2 General Level.
10 Ability to convey the process and results of their studies systematically and clearly in written and oral form in national and international environments.
11 To know the social, environmental, health, security, law dimensions, project management and business life applications of engineering applications and to be aware of the constraints of their engineering applications.
12 Ability to observe social, scientific and ethical values in the stages of data collection, interpretation and announcement and in all professional 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