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İzmir Ekonomi Üniversitesi

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    GRADUATE SCHOOL

    M.SC. in Computer Engineering (Without Thesis)

    EEE 601 | Course Introduction and Application Information

    Course Name
    Fast Filtering Algorithms
    Code
    Semester
    Theory
    (hour/week)
    Application/Lab
    (hour/week)
    Local Credits
    ECTS
    EEE 601
    Fall/Spring
    3
    0
    3
    7.5

    Prerequisites
    None
    Course Language
    English
    Course Type
    Elective
    Course Level
    Third 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 aim is to understand the relations between wavelets, filter banks, and multirate systems in area of signal processing and gain the skill in the area of time-frequency analysis of the continuous and discrete signals.
    Learning Outcomes

    The students who succeeded in this course;

    • Understand the relation between wavelets, filter banks, and multirate systems,
    • Be able to perform time-frequency analysis,
    • Be able to develop fast wavelet algorithms using Matlab,
    • Learn limits of various filters used in different applications..
    • Students will
    Course Description The course will cover fast wavelet transform algorithms – relation to filter banks, wavelet packets construction of wavelets, biorthogonality and biorthogonal basis, biorthogonal system of wavelets - construction, and the lifting scheme.

     



    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 Discrete-time Filters A Wavelet Tour of Signal Processing, Mallat, Ch. 3
    2 Sampling Rate Change Operations A Wavelet Tour of Signal Processing, Mallat, Ch. 3
    3 Filter Banks A Wavelet Tour of Signal Processing, Mallat, Ch. 7
    4 Perfect Reconstruction A Wavelet Tour of Signal Processing, Mallat, Ch. 7
    5 Modulation and Polyphase Representations A Wavelet Tour of Signal Processing, Mallat, Ch. 7
    6 MATLAB® Wavelet Toolbox
    7 Orthogonal Filter Banks A Wavelet Tour of Signal Processing, Mallat, Ch. 7
    8 Midterm
    9 Maxflat Filters The course slides
    10 Multiresolution Analysis A Wavelet Tour of Signal Processing, Mallat, Ch. 9
    11 Orthogonal Wavelet Bases The course slides
    12 Mallat Pyramid Algorithm The course slides
    13 Accuracy of Wavelet Approximations The course slides
    14 Convergence of the Cascade Algorithm The course slides
    15 Wavelet Compression Algorithms The course slides
    16 Review of the Semester  

     

    Course Notes/Textbooks The textbook referenced above and course
    Suggested Readings/Materials Related Research Papers

     

    EVALUATION SYSTEM

    Semester Activities Number Weigthing
    Participation
    Laboratory / Application
    Field Work
    Quizzes / Studio Critiques
    Portfolio
    Homework / Assignments
    4
    20
    Presentation / Jury
    Project
    1
    40
    Seminar / Workshop
    Oral Exams
    Midterm
    1
    40
    Final Exam
    Total

    Weighting of Semester Activities on the Final Grade
    60
    Weighting of End-of-Semester Activities on the Final Grade
    40
    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
    4
    15
    60
    Presentation / Jury
    0
    Project
    1
    35
    35
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    1
    22
    22
    Final Exam
    0
        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.
    -
    -
    -
    X
    -
    2 Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.
    -
    -
    X
    -
    -
    3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines.
    -
    -
    -
    X
    -
    4 Is informed about new and upcoming applications in the field and learns them whenever necessary.
    -
    -
    X
    -
    -
    5 Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.
    -
    -
    -
    -
    X
    6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.
    -
    -
    -
    -
    X
    7 Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process.
    X
    -
    -
    -
    -
    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.
    -
    -
    -
    -
    X
    9 Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.
    X
    -
    -
    -
    -
    10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
    -
    -
    X
    -
    -
    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.
    X
    -
    -
    -
    -
    12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.
    X
    -
    -
    -
    -

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

     

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