ACADEMICS
Course Details
ELE 407 Digital Signal Processing
2020-2021 Spring term information
The course is not open this term
Timing data are obtained using weekly schedule program tables. To make sure whether the course is cancelled or time-shifted for a specific week one should consult the supervisor and/or follow the announcements.
Course definition tables are extracted from the ECTS Course Catalog web site of Hacettepe University (http://akts.hacettepe.edu.tr) in real-time and displayed here. Please check the appropriate page on the original site against any technical problems. Course data last updated on 24/02/2021.
ELE407 - DIGITAL SIGNAL PROCESSING
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| DIGITAL SIGNAL PROCESSING | ELE407 | 7th Semester | 3 | 0 | 3 | 6 |
| Prerequisite(s) | ELE301 Signals and Systems | |||||
| Course language | English | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Question and Answer Drill and Practice Other: This course must be taken together with ELE409 DIGITAL SIGNAL PROCESSING LABORATORY. | |||||
| Instructor (s) | Faculty members | |||||
| Course objective | Successful students are expected to gain the following abilities: Knowledge of basic mathematical analysis and signal processing methods, processing of signals both in time and frequency domains. | |||||
| Learning outcomes |
| |||||
| Course Content | Discrete-time signals and systems. Difference equation representation. Sampling, decimation, interpolation. Review of the Z-transform. Transform analysis of linear, time-invariant systems. Structures for discrete-time systems. Effects of quantization. Infinite impulse response (IIR) and finite impulse response (FIR) filter design techniques. The discrete Fourier series, the discrete Fourier transform and Fast Fourier transform. Intoduction to two dimensional signals and systems. | |||||
| References | 1- Oppenheim, A.V. and R.W. Schafer , Discrete-time Signal Processing.Pearson, 2010. 2- Lecture Notes. | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Review of Discrete-time signals, systems, Fourier, Z-tr. |
| Week 2 | Sampling, Decimation, Interpolation. |
| Week 3 | Diffrence Equation Representation, Frequency Response . |
| Week 4 | Relation Between Magnitude and Phase, Inverse systems, All-pass Systems. |
| Week 5 | Flow Graph Realization. |
| Week 6 | Quantization |
| Week 7 | Term Exam 1 |
| Week 8 | Analog Butterworth and Chebyshev Filter Design. |
| Week 9 | Digital Butterworth and Chebyshev Filter Design, FIR Filter Design |
| Week 10 | Discrete-time Fourier Series, DFT, Properties of DFT. |
| Week 11 | Convolution with DFT (Overlap-add/save). |
| Week 12 | Fast Fourier Transform. |
| Week 13 | Term Exam 2 |
| Week 14 | 2-D Signal Processing. |
| Week 15 | Preparation for Final exam |
| Week 16 | Final exam |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 0 | 0 |
| Laboratory | 0 | 0 |
| Application | 0 | 0 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 0 | 0 |
| Presentation | 0 | 0 |
| Project | 0 | 0 |
| Seminar | 0 | 0 |
| Midterms | 2 | 50 |
| Final exam | 1 | 50 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 0 | 50 |
| Percentage of final exam contributing grade succes | 0 | 50 |
| Total | 100 | |
Workload and ECTS calculation
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 14 | 3 | 42 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 14 | 6 | 84 |
| Presentation / Seminar Preparation | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Homework assignment | 0 | 0 | 0 |
| Midterms (Study duration) | 2 | 10 | 20 |
| Final Exam (Study duration) | 1 | 25 | 25 |
| Total Workload | 31 | 44 | 171 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. PO1. Possesses the theoretical and practical knowledge required in Electrical and Electronics Engineering discipline. | X | ||||
| 2. PO2. Utilizes his/her theoretical and practical knowledge in the fields of mathematics, science and electrical and electronics engineering towards finding engineering solutions. | X | ||||
| 3. PO3. Determines and defines a problem in electrical and electronics engineering, then models and solves it by applying the appropriate analytical or numerical methods. | X | ||||
| 4. PO4. Designs a system under realistic constraints using modern methods and tools. | X | ||||
| 5. PO5. Designs and performs an experiment, analyzes and interprets the results. | X | ||||
| 6. PO6. Possesses the necessary qualifications to carry out interdisciplinary work either individually or as a team member. | X | ||||
| 7. PO7. Accesses information, performs literature search, uses databases and other knowledge sources, follows developments in science and technology. | X | ||||
| 8. PO8. Performs project planning and time management, plans his/her career development. | X | ||||
| 9. PO9. Possesses an advanced level of expertise in computer hardware and software, is proficient in using information and communication technologies. | X | ||||
| 10. PO10. Is competent in oral or written communication; has advanced command of English. | X | ||||
| 11. PO11. Has an awareness of his/her professional, ethical and social responsibilities. | X | ||||
| 12. PO12. Has an awareness of the universal impacts and social consequences of engineering solutions and applications; is well-informed about modern-day problems. | X | ||||
| 13. PO13. Is innovative and inquisitive; has a high level of professional self-esteem. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest