Course Details

ELE409 - Digital Signal Processing Laboratory

2023-2024 Spring term information
The course is not open this term
ELE409 - Digital Signal Processing Laboratory
Program Theoretưcal hours Practical hours Local credit ECTS credit
Undergraduate 0 3 1 2
Obligation : Elective
Prerequisite courses : -
Concurrent courses : ELE407
Delivery modes : Face-to-Face
Learning and teaching strategies : Lecture, Question and Answer, Experiment, Other: This course must be taken together with ELE407 DIGITAL SIGNAL PROCESSING.
Course objective : Successful students are expected to know application of time domain and frequency domain signal processing methods in Matlab, Labview or similar environment.
Learning outcomes : A student completing the course successfully will Recognize basic signal processing problems, Model encountered problems, Know which algorithms can be used to solve the problem, know the advantages and disadvantages of these algorithms, and implement them by writing programs, Apply the techniques and algorithms learnt in the class to problems encountered in projects , Have adequate knowledge to follow and understand other signal processing algorithms.
Course content : Sampling, decimation and interpolation. Reconstruction and effects of aliasing. Design and implementation of digital filters. Quantization and effects of quantization on Digital systems. Windowing functions and their properties. Implementation and investigation of discrete Fourier transform and Fast Fourier transform algorithms. Experiments using speech and image signals.
References : 1. Oppenheim , A.V. and R.W. Schafer, Discrete-time Signal Processing, .Pearson, 2010.; 2. Lecture Notes.
Course Outline Weekly
Weeks Topics
1 DFT , Upsampling, Downsampling
2 Analysis of Discrete-Time Systems
3 Effect of Quantization and Phase Shift
4 IIR Filter Design
5 Windowing and FIR Filter Design
6 Discrete-Time Filtering using DFT
7 Image Processing
8 Preparation for Final exam
9 Final Exam
Assessment Methods
Course activities Number Percentage
Attendance 0 0
Laboratory 7 50
Application 0 0
Field activities 0 0
Specific practical training 0 0
Assignments 0 0
Presentation 0 0
Project 0 0
Seminar 0 0
Quiz 0 0
Midterms 0 0
Final exam 1 50
Total 100
Percentage of semester activities contributing grade success 50
Percentage of final exam contributing grade success 50
Total 100
Workload and ECTS Calculation
Course activities Number Duration (hours) Total workload
Course Duration 0 0 0
Laboratory 7 3 21
Application 0 0 0
Specific practical training 0 0 0
Field activities 0 0 0
Study Hours Out of Class (Preliminary work, reinforcement, etc.) 7 4 28
Presentation / Seminar Preparation 0 0 0
Project 0 0 0
Homework assignment 0 0 0
Quiz 0 0 0
Midterms (Study Duration) 0 0 0
Final Exam (Study duration) 1 12 12
Total workload 15 19 61
Matrix Of The Course Learning Outcomes Versus Program Outcomes
Key learning outcomes Contribution level
1 2 3 4 5
1. Possesses the theoretical and practical knowledge required in Electrical and Electronics Engineering discipline.
2. Utilizes his/her theoretical and practical knowledge in the fields of mathematics, science and electrical and electronics engineering towards finding engineering solutions.
3. Determines and defines a problem in electrical and electronics engineering, then models and solves it by applying the appropriate analytical or numerical methods.
4. Designs a system under realistic constraints using modern methods and tools.
5. Designs and performs an experiment, analyzes and interprets the results.
6. Possesses the necessary qualifications to carry out interdisciplinary work either individually or as a team member.
7. Accesses information, performs literature search, uses databases and other knowledge sources, follows developments in science and technology.
8. Performs project planning and time management, plans his/her career development.
9. Possesses an advanced level of expertise in computer hardware and software, is proficient in using information and communication technologies.
10. Is competent in oral or written communication; has advanced command of English.
11. Has an awareness of his/her professional, ethical and social responsibilities.
12. Has an awareness of the universal impacts and social consequences of engineering solutions and applications; is well-informed about modern-day problems.
13. Is innovative and inquisitive; has a high level of professional self-esteem.
1: Lowest, 2: Low, 3: Average, 4: High, 5: Highest
General Information | Course & Exam Schedules | Real-time Course & Classroom Status
Undergraduate Curriculum | Minor Program For Non-departmental Students | Open Courses, Sections and Supervisors | Weekly Course Schedule | Examination Schedules | Information for Registration | Prerequisite and Concurrent Courses | Legal Info and Documents for Internship | Academic Advisors for Undergraduate Program | Information for ELE 401-402 Graduation Project | Virtual Exhibitions of Graduation Projects | Erasmus+ Program | Program Educational Objectives & Student Outcomes | ECTS Course Catalog | HU Registrar's Office
Graduate Curriculum | Open Courses and Supervisors | Weekly Course Schedule | Final Examinations Schedule | Schedule of Graduate Thesis Defences and Seminars | Information for Registration | ECTS Course Catalog - Master's Degree | ECTS Course Catalog - PhD Degree | HU Graduate School of Science and Engineering