ECTS - Digital Signal Processing
Digital Signal Processing (EE306) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Digital Signal Processing | EE306 | 3 | 2 | 0 | 4 | 6 |
| Pre-requisite Course(s) |
|---|
| EE 303 |
| Course Language | English |
|---|---|
| Course Type | N/A |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Demonstration, Discussion, Question and Answer, Drill and Practice. |
| Course Lecturer(s) |
|
| Course Objectives | •Understand how analog signals are represented by their discrete-time samples, and in what ways digital filtering is equivalent to analog filtering. •Master the representation of discrete-time signals in the frequency domain, using the notions of z-transform, discrete-time Fourier transform and discrete Fourier transform (DFT). •Learn the basic forms of FIR and IIR filters, and how to design filters with desired frequency responses. •Understand the implementation of the DFT in terms of the FFT, as well as some of its applications (computation of convolution sums, spectral analysis) |
| Course Learning Outcomes |
The students who succeeded in this course;
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| Course Content | Signals and signal processing, discrete-time signals and systems, discrete-time Fourier transform (DTFT) and computation of the DFT, the z-Transform, sampling of continuous-time signals, transform analysis of linear time-invariant (LTI) systems, structures for discrete-time systems, digital filter design techniques, discrete Fourier transform, app |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Discrete-Time (DT) Signals and Systems •DT signals: Sequences •DT systems: Memoryless, Linear, Time-Invariant, Causal, and Stable Systems •Frequency-Domain Representation of DT Signals and Systems | Glance this week’s topics from the lecture |
| 2 | DT Signals and Systems | Review last week and glance this week’s topics from the lecture |
| 3 | The z-Transform •Properties of the Region of Convergence (ROC) for the z-transform •The Inverse z-transform •z-transform Properties | Glance this week’s topics from the lecture |
| 4 | The z-Transform | Review last week and glance this week’s topics from the lecture Glance this week’s topics from the lecture |
| 5 | Transform Analysis of Linear Time-Invariant (LTI) Systems •The Frequency Response of LTI Systems: Ideal frequency-selective filters, Phase Distortion and Delay •System Functions: Stability, Causality, Inverse Systems, Impulse Response for Rational System Functions •Relationship between Magnitude and Phase •All-Pass Systems •Minimum-Phase Systems •Linear Systems with Generalized Linear Phase | Glance this week’s topics from the lecture |
| 6 | Transform Analysis of LTI Systems | Review last week and glance this week’s topics from the lecture |
| 7 | Structures for Discrete-Time Systems •Block Diagram Representation of Linear Constant-Coefficient Difference Equations •Signal Flow Graph •Basic Structures for IIR Systems: Direct, Cascade, and Parallel Forms | Glance this week’s topics from the lecture |
| 8 | Structures for Discrete-Time Systems •Basic Network Structures for FIR Systems | Review last week and glance this week’s topics from the lecture |
| 9 | Filter Design Techniques •Prototype Analog Filters: Butterworth, Chebyshev, and Elliptic Filters •Design of DT IIR Filters from CT Filters: Impulse Invariance method, Bilinear Transformations | Glance this week’s topics from the lecture |
| 10 | Filter Design Techniques •Design of FIR Filters by Windowing | Review last week and glance this week’s topics from the lecture |
| 11 | The Discrete Fourier Transform (DFT) •Relationship between DFT and Discrete Cosine Transform (DCT) | Glance this week’s topics from the lecture |
| 12 | The DFT | Review last week and glance this week’s topics from the lecture |
| 13 | Applications to Speech and Image Processing | Glance this week’s topics from the lecture |
| 14 | Applications to Speech and Image Processing | Glance this week’s topics from the lecture |
| 15 | Final examination period | Review topics |
| 16 | Final examination period | Review topics |
Sources
| Course Book | 1. Discrete-Time Signal Processing, Second Edition, Alan V. Oppenheim, Ronald W. Schafer and John R. Buck, Prentice Hall, 1999 |
|---|---|
| Other Sources | 2. Digital Signal Processing , A Computer Based Approach, Sanjit. K. Mitra, McGraw-Hill, 1998 |
| 3. Digital Signal Processing, Algorithms and Applications, John G. Proakis and Dimitris G.Manolakis,3rd Edition, 2000 |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | 4 | 20 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 2 | 40 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 7 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Adequate knowledge of subjects related to mathematics, natural sciences, and Electrical and Electronics Engineering discipline; ability to apply theoretical and applied knowledge in those fields to the solution of complex engineering problems. | X | ||||
| 2 | An ability to identify, formulate, and solve complex engineering problems, ability to choose and apply appropriate models and analysis methods for this. | X | ||||
| 3 | An ability to design a system, component, or process under realistic constraints to meet desired needs, and ability to apply modern design approaches for this. | X | ||||
| 4 | The ability to select and use the necessary modern techniques and tools for the analysis and solution of complex problems encountered in engineering applications; the ability to use information technologies effectively | X | ||||
| 5 | Ability to design and conduct experiments, collect data, analyze and interpret results for investigating complex engineering problems or discipline-specific research topics. | X | ||||
| 6 | An ability to function on multi-disciplinary teams, and ability of individual working. | X | ||||
| 7 | Ability to communicate effectively orally and in writing; knowledge of at least one foreign language; active report writing and understanding written reports, preparing design and production reports, the ability to make effective presentation the ability to give and receive clear and understandable instructions. | X | ||||
| 8 | Awareness of the necessity of lifelong learning; the ability to access knowledge, follow the developments in science and technology and continuously stay updated. | X | ||||
| 9 | Acting compliant with ethical principles, professional and ethical responsibility, and knowledge of standards used in engineering applications. | X | ||||
| 10 | Knowledge about professional activities in business, such as project management, risk management, and change management awareness of entrepreneurship and innovation; knowledge about sustainable development. | X | ||||
| 11 | Knowledge about the impacts of engineering practices in universal and societal dimensions on health, environment, and safety. the problems of the current age reflected in the field of engineering; awareness of the legal consequences of engineering solutions. | X | ||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | 4 | 2 | 8 |
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 5 | 80 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 4 | 8 |
| Prepration of Final Exams/Final Jury | 1 | 5 | 5 |
| Total Workload | 149 | ||