EEE4501 Digital Signal ProcessingBahçeşehir UniversityDegree Programs ELECTRICAL AND ELECTRONICS ENGINEERINGGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ELECTRICAL AND ELECTRONICS ENGINEERING
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
EEE4501 Digital Signal Processing Fall 3 2 4 6
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Departmental Elective
Course Level: Bachelor’s Degree (First Cycle)
Mode of Delivery: Face to face
Course Coordinator : Dr. Öğr. Üyesi ZAFER İŞCAN
Recommended Optional Program Components: None
Course Objectives: The course will provide the students with the understanding of how to analyze and manipulate digital signals, and the fundamental programming knowledge and experience to do so.

Learning Outcomes

The students who have succeeded in this course;
1. Identify if a system is a Linear Time-Invariant (LTI) System.
2. Describe signals and systems using Linear Constant Coefficient Difference Equations.
3. Define Fourier representations of signals and systems.
4. Demonstrate how to find the Z-transform of a LTI system.
5. Describe the relationship between poles, zeros, and stability.
6. Describe the Sampling Theorem and how this relates to Aliasing and Folding.
7. Define multirate signal processing concepts.
8. Demostrate skills to design, analyze, and implement digital filters in Matlab.
9. Determine the frequency response of FIR and IIR filters.
10. Determine the spectrum of a signal using the DFT, FFT and spectrogram.
11. Demonstrate DCT of a signal and ceptrum analysis.

Course Content

Introduction to Matlab; Discrete-Time Signals and Systems; Linear Constant Coefficient Difference Equations, Fourier Transform; Z-Transform; LTI Discrete-Time Systems in the Transform Domain; Digital Processing of Continuous-Time Signals, Sampling; Multirate Signal Processing; Laplace Transform; Digital Filter Design; Linear Prediction, Discrete Fourier Transform; Discrete Cosine Transform; Cepstrum Analysis

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Meeting, Discussion of the Course, Introduction to MATLAB
2) Introduction to Digital Signal Processing Discrete-Time Signals and Systems [Mitra] Chapter 1 [Mitra] Chapter 2 [OppenheimSchafer] Chapter 2.0-2.6
3) Linear Constant Coefficient Difference Equations Fourier Transform [Mitra] Chapter 2.7-2.9, 3.1-3.6 [OppenheimSchafer] Chapter 2.5-2.9
4) Z-Transform [Mitra] Chapter 6 [OppenheimSchafer] Chapter 3
5) LTI Discrete-Time Systems in the Transform Domain [Mitra] Chapter 7 [OppenheimSchafer] Chapter 5
6) Digital Processing of Continuous-Time Signals Sampling [Mitra] Chapter 4 [OppenheimSchafer] Chapter 4.1-4.6
7) Multirate Signal Processing [Mitra] Chapter 13 [OppenheimSchafer] Chapter 4.7-4.9
8) Laplace Transform Slides Various resources
9) Midterm Exam. Discussion and solutions of the questions.
10) Digital Filter Design [Mitra] Chapter 8, 9, 10 [OppenheimSchafer] Chapter 7
11) Linear Prediction Slides Various resources
12) Discrete Fourier Transform [Mitra] Chapter 5.2-5.10 [OppenheimSchafer] Chapter 8
13) Discrete Cosine Transform [Mitra] Chapter 5.11 [OppenheimSchafer] Chapter 8.8
14) Cepstrum Analysis Overview and Wrap-up [OppenheimSchafer] Chapter 13
15) Course Project Presentations and Demonstrations

Sources

Course Notes / Textbooks: Discrete-Time Signal Processing, Alan V. Oppenheim and Ronald W. Schafer, Third Edition, Pearson, 2010.
References: Digital Signal Processing: A Computer-based Approach, Sanjit K.Mitra, Third Edition, McGraw-Hill 2006.

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance 14 % 5
Homework Assignments 5 % 5
Project 1 % 20
Midterms 1 % 30
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 40
PERCENTAGE OF FINAL WORK % 60
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Application 10 3 30
Study Hours Out of Class 17 3 51
Presentations / Seminar 1 1 1
Project 6 4 24
Quizzes 2 0 0
Midterms 1 2 2
Final 1 2 2
Total Workload 152

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Adequate knowledge in mathematics, science and electric-electronic engineering subjects; ability to use theoretical and applied information in these areas to model and solve engineering problems. 4
2) Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. 2
3) Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues, according to the nature of the design.) 2
4) Ability to devise, select, and use modern techniques and tools needed for electrical-electronic engineering practice; ability to employ information technologies effectively. 2
5) Ability to design and conduct experiments, gather data, analyze and interpret results for investigating engineering problems. 5
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. 2
7) Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing. 5
8) Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. 3
9) Awareness of professional and ethical responsibility. 1
10) Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11) Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions. 2