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Syllabus ( ELEC 567 )

   Basic information
Course title: Digital Signal Processing
Course code: ELEC 567
Lecturer: Assist. Prof. Köksal HOCAOĞLU
ECTS credits: 7.5
GTU credits: 3 (3+0+0)
Year, Semester: 1/2, Fall and Spring
Level of course: Second Cycle (Master's)
Type of course: Area Elective
Language of instruction: Turkish
Mode of delivery: Face to face
Pre- and co-requisites: Undergraduate course in signals and systems. Also, the ability to program is essential to complete the computer projects. The projects can be done using MATLAB.
Professional practice: No
Purpose of the course: The primary goal of this course is three-folded: (1) to introduce signals, systems, their time- and frequency-domain representations and the associated mathematical tools that are fundamental to all DSP techniques; (2) to provide a working knowledge of the design, implementation and analysis of digital filters; (3) to provide a working knowledge of modeling and analysis of signals based on spectral estimation techniques. The goal is to also provide the student with the necessary background for taking advanced level courses in signal processing.
   Learning outcomes Up

Upon successful completion of this course, students will be able to:

  1. Determine the filter specifications by analyzing the real world digital signal processing problems, and design the filter accordingly

    Contribution to Program Outcomes

    1. Define and manipulate advanced concepts of Electronics Engineering
    2. Formulate and solve advanced engineering problems

    Method of assessment

    1. Written exam
    2. Homework assignment
    3. Term paper
  2. Analyze and model digital signals

    Contribution to Program Outcomes

    1. Define and manipulate advanced concepts of Electronics Engineering
    2. Formulate and solve advanced engineering problems

    Method of assessment

    1. Written exam
    2. Homework assignment
  3. Implement discrete-time systems

    Contribution to Program Outcomes

    1. Define and manipulate advanced concepts of Electronics Engineering
    2. Formulate and solve advanced engineering problems
    3. Acquire scientific knowledge

    Method of assessment

    1. Homework assignment
    2. Term paper
  4. Alter the sampling rate of a signal using decimation and interpolation

    Contribution to Program Outcomes

    1. Formulate and solve advanced engineering problems

    Method of assessment

    1. Term paper
  5. Implement digital signal processing methods based on a given algorithmic description or theory

    Contribution to Program Outcomes

    1. Formulate and solve advanced engineering problems
    2. Develop an awareness of continuous learning in relation with modern technology

    Method of assessment

    1. Term paper
   Contents Up
Week 1: Introduction to digital signal processing
Week 2: Discrete time systems
Week 3: Discrete time systems
Week 4: Z transform
Week 5: Discrete time Fourier transform
Week 6: Mid term exam
Week 7: FIR filter design
Week 8: IIR filter design
Week 9: Spectral estimation: background
Week 10: Spectral estimation: parametric methods
Week 11: Spectral estimation: non-parametric methods
Week 12: Adaptive signal processing
Week 13: Adaptive signal processing
Week 14: Presentation of term project to class
Week 15*: Review
Week 16*: Final Exam
Textbooks and materials: Alan V. Oppenheim, Ronald W. Schafer, Discrete-Time Signal Processing, 3rd Edition, Prentice Hall
Recommended readings: 1. J.G. Proakis and D.G. Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications, Prentice-Hall, NJ, Fourth Edition, 2007
2. A.V. Oppenheim and A.S. Willsky with Hamid Nawab, Signals & Systems, Prentice Hall, 2. Edition, 1997.
3. Vinay K. Ingle, John G. Proakis, Digital Signal Processing Using MATLAB, Thomson Learning, 2. Edition, 2006
4. P. Stoica and R. Moses, Spectral Analysis of Signals, Prentice-Hall, NJ, USA, 2005
5. Kay, Modern Spectral Estimation, Prentice-Hall, 1988
6. S L Marple, Digital spectral analysis: with applications, Prentice-Hall, NJ, USA, 1986
7. S. Haykin, Adaptive Filter Theory, Prentice-Hall, 2002.
  * Between 15th and 16th weeks is there a free week for students to prepare for final exam.
Assessment Up
Method of assessment Week number Weight (%)
Mid-terms: 6 20
Other in-term studies: 0
Project: 14 25
Homework: 2,3,4,7,8 25
Quiz: 0
Final exam: 16 30
  Total weight:
(%)
   Workload Up
Activity Duration (Hours per week) Total number of weeks Total hours in term
Courses (Face-to-face teaching): 3 14
Own studies outside class: 5 12
Practice, Recitation: 0 0
Homework: 4 6
Term project: 18 2
Term project presentation: 1 1
Quiz: 0 0
Own study for mid-term exam: 12 1
Mid-term: 1 1
Personal studies for final exam: 15 1
Final exam: 2 1
    Total workload:
    Total ECTS credits:
*
  * ECTS credit is calculated by dividing total workload by 25.
(1 ECTS = 25 work hours)
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