İzmir Ekonomi Üniversitesi
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  • GRADUATE SCHOOL

    M.SC. in Computer Engineering (Without Thesis)

    EEE 551 | Course Introduction and Application Information

    Course Name
    Linear Systems Theory
    Code
    Semester
    Theory
    (hour/week)
    Application/Lab
    (hour/week)
    Local Credits
    ECTS
    EEE 551
    Fall/Spring
    3
    0
    3
    7.5

    Prerequisites
    None
    Course Language
    English
    Course Type
    Elective
    Course Level
    Second Cycle
    Mode of Delivery -
    Teaching Methods and Techniques of the Course -
    National Occupation Classification -
    Course Coordinator
    Course Lecturer(s)
    Assistant(s) -
    Course Objectives The course aims the students: i) to get a solid mathematical background on real analysis, normed linear spaces and linear differential equations in the state form. ii) to gain basic skills in analyzing a given linear time-invariant dynamical system; determining whether or not the system has a well-defined solution, so analyzing qualitative properties of solutions, and analyzing the stability, controllability and observability of linear dynamical systems, and iii) to have a dynamical system view.
    Learning Outcomes

    The students who succeeded in this course;

    • Prove the facts related to the algebraic stuructures, especially normed linear spaces using their properties
    • Determine eigenvalues, eigenvectors, null space and range space for a matrix.
    • Determine the solutions and state transition matrix for state equations
    • Analyze stability, controllability and observability
    Course Description Real analysis. Algebraic structures. Linear spaces and transformations. State equations. Existence and uniqueness of solutions. Properties of dynamical systems. State transition matrix for linear time-invariant systems. Zero-state solutions. Zero-input solutions. Minimal polynomial and Cayley-Hamilton theorem. Eigenvalues and eigenvectors. Jordan form. Stability in the sense of Liapunov.Bounded-Input Bounded-Output Stability. Controllablity and observability. Minimal realization.

     



    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 Set theory overview. Ordering relation. Greatest and least elements Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    2 Algebraic structures: Group, ring, field and linear space. Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    3 Normed, metric and inner-product spaces. Vector and matrix norms. Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    4 Derivation of state equations from systems. Existence and uniqueness of solutions. Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    5 Fundamental matrix and state transition matrix of linear state equations. Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    6 Zero-input, zero-state and complete solutions. Impulse response matrix. Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    7 Benzerlik dönüşümü ile köşegenleştirme. Rezidü matrisleri. Karakteristik ve minimal polinaomlar. Cayley-Hamilton Teoremi. Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    8 Generalized eigenvalues and Jordan form for state matrix. Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    9 1. Midterm
    10 Liapunov stability of linear time-invariant and time-varying systems. Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    11 Liapunov stability of linear time-invariant and time-varying systems. Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    12 Controllability of linear time-invariant and time-varying systems. Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    13 2. Midterm
    14 Controllability of linear time-invariant and time-varying systems. Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    15 Minimal realization of linear time-invariant dynamical systems. Deseor, C. A. (1970) Notes for a Second Course on Linear Systems, Van Nostrand Reinhold.
    16 Review of the Semester  

     

    Course Notes/Textbooks The textbook referenced above and lecture notes
    Suggested Readings/Materials Related Books

     

    EVALUATION SYSTEM

    Semester Activities Number Weigthing
    Participation
    1
    10
    Laboratory / Application
    Field Work
    Quizzes / Studio Critiques
    Portfolio
    Homework / Assignments
    Presentation / Jury
    Project
    Seminar / Workshop
    Oral Exams
    Midterm
    2
    40
    Final Exam
    1
    50
    Total

    Weighting of Semester Activities on the Final Grade
    3
    50
    Weighting of End-of-Semester Activities on the Final Grade
    1
    50
    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
    10
    0
    Presentation / Jury
    5
    0
    Project
    0
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    2
    40
    80
    Final Exam
    1
    37
    37
        Total
    225

     

    COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

    #
    PC Sub Program Competencies/Outcomes
    * Contribution Level
    1
    2
    3
    4
    5
    1 Accesses information in breadth and depth by conducting scientific research in Computer Engineering, evaluates, interprets and applies information.
    -
    -
    -
    -
    -
    2 Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.
    -
    -
    -
    -
    -
    3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines.
    -
    -
    -
    -
    -
    4 Is informed about new and upcoming applications in the field and learns them whenever necessary.
    -
    -
    -
    -
    -
    5 Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.
    -
    -
    -
    -
    -
    6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.
    -
    -
    -
    -
    -
    7 Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process.
    -
    -
    -
    -
    -
    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.
    -
    -
    -
    -
    -
    9 Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.
    -
    -
    -
    -
    -
    10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
    -
    -
    -
    -
    -
    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.
    -
    -
    -
    -
    -
    12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.
    -
    -
    -
    -
    -

    *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

     


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