COURSE INTRODUCTION AND APPLICATION INFORMATION


Course Name
Digital Signal Processing
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
EEE 413
Fall/Spring
2
2
3
6
Prerequisites
 EEE 301To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Elective
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives The main objective of this course is to introduce the fundamental concepts of mathematical tools in digital signal processing and linear systems analysis with examples from signal processing, communications, and control. Representation, analysis, and design of discrete time signals and systems. Discretetime processing of continuoustime signals. Frequency domain representations: Fourier series and transforms. Decimation, interpolation, and sampling rate conversion. Flowgraph structures for DT systems. Time and frequencydomain design techniques for recursive (IIR) and nonrecursive (FIR) filters. Linear prediction. Connection between continuous and discrete time frequency representations. Discrete Fourier transform (DFT) and fast Fourier transform (FFT). Shorttime Fourier analysis and filter banks.
Learning Outcomes The students who succeeded in this course;
  • Explain the Z-transform and its application to the analysis of discrete-time LTI systems,
  • Apply design techniques for FIR and IIR type digital filters,
  • Describe the discrete Fourier transform (DFT) and its applications,
  • Explain FFT algorithms for efficient computation of the DFT,
  • Describe the significance of digital signal processing in the fields of telecommunications, computing, and other areas of Electrical and Electronics Engineering,
  • Simulate the Matlab and its signal processing toolbox for desinging and analyzing digital signal processing systems (i.e. Digital filters).
Course Description Topics covered in class mainly include principles and applications of digital signal processing. Representation, analysis, and design of digital signals and systems. Discretetime processing of continuoustime signals. Frequency domain representations: Fourier series and transforms. Decimation, interpolation, and sampling rate conversion. Time and frequencydomain design techniques for recursive (IIR) and nonrecursive (FIR) filters. Discrete Fourier transform (DFT) and fast Fourier transform (FFT). Shorttime Fourier analysis and filter banks.
Related Sustainable Development Goals

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Introduction Chapter 1. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
2 Discrete-time signals and systems Chapter 2.1-2.2. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
3 LTI systems; Properties of LTI systems; Difference equations Chapter 2.3-2.5. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
4 Discrete-time Fourier Transform; Frequency domain representation Chapter 2.6-2.9. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
5 The z-transform; Properties; Inverse z-transform; Partial fraction expansion Chapter 3.1-3.4. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
6 Analysis of LTI systems in z-domain; the unilateral z-transform Chapter 3.5-3.6. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
7 Transform analysis of LTI systems; System functions; Stability and causality Chapter 5.1-5.2. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
8 Frequency response of LTI systems; All-pass and minimum-phase systems; Generalized linear phase Chapter 5.3-5.7. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
9 Structures for IIR and FIR systems; Signal flow graph representation Chapter 6.1-6.6. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
10 Design of IIR filters from analog filters; Frequency transformations; Design examples Chapter 7.1-7.4. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
11 Design of FIR filters; Kaiser window method; The Parks-McClellan algortihm; Design examples Chapter 7.5-7.8. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
12 The Discrete Fourier Series (DFS);The Discrete Fourier Transform (DFT); Circular convolution; Linear convolution using DFT Chapter 8.1-8.7. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
13 Computation of the DFT; Decimation-in-time and decimation-in-frequency FFT algorithms Chapter 9.1-9.3. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
14 Spectral analysis with the DFT; The Periodogram; Power spectrum estimation Chapter 10.1-10.5. DiscreteTime Signal Processing. Oppenheim & Schafer. ISBN 9780132067096.
15 Final exam review Lecture notes
16 Review of the Semester  
Course Notes/Textbooks A. V. Oppenheim, R. W. Schafer, “DiscreteTime Signal Processing”, 3rd Ed., Pearson International Edition, Upper Saddle River, NJ 07458, 2010, ISBN 9780132067096.
Suggested Readings/Materials J.G.Proakis, D.G. Manolakis, “Digital Signal Processing”, 4th Ed., Pearson International Edition, Upper Saddle River, NJ 07458, 2007. ISBN 9780131873741.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
-
-
Laboratory / Application
1
30
Field Work
Quizzes / Studio Critiques
-
-
Portfolio
Homework / Assignments
Presentation / Jury
Project
-
-
Seminar / Workshop
Oral Exam
Midterm
1
30
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
2
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
2
32
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
2
Study Hours Out of Class
16
3
48
Field Work
Quizzes / Studio Critiques
-
-
Portfolio
Homework / Assignments
-
-
Presentation / Jury
Project
-
Seminar / Workshop
Oral Exam
Midterms
1
30
Final Exams
1
38
    Total
180

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science and Biomedical Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

2

To be able to identify, define, formulate, and solve complex Biomedical Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

3

To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

4

To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Biomedical Engineering applications.

5

To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Biomedical Engineering research topics.

6

To be able to work efficiently in Biomedical Engineering disciplinary and multi-disciplinary teams; to be able to work individually.

7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions.

8

To have knowledge about global and social impact of Biomedical Engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of engineering solutions.

9

To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications.

10

To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Biomedical Engineering, and to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Biomedical Engineering.

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