ACADEMICS
Course Detail

ELE 409 Digital Signal Processing Laboratory
2017-2018 Fall term information

The course is open this term
Section: 21-25
Supervisor(s):Dr. Umut Sezen
Assistant(s):Ömer Haliloğlu
Cansu Sunu
Dr. Barış Yüksekkaya
Mevlüt Said Saraçoğlu
PlaceDayHours
-

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://ects.hacettepe.edu.tr) in real-time and displayed here. Please check the appropriate page on the original site against any technical problems.

ELE409 - DIGITAL SIGNAL PROCESSING LABORATORY

Course Name Code Semester Theory
(hours/week)
Application
(hours/week)
Credit ECTS
DIGITAL SIGNAL PROCESSING LABORATORY ELE409 7th Semester 0 3 1 2
Prerequisite(s)
Course languageEnglish
Course typeElective 
Mode of DeliveryFace-to-Face 
Learning and teaching strategiesLecture
Question and Answer
Experiment
Other: This course must be taken together with ELE407 DIGITAL SIGNAL PROCESSING.  
Instructor (s)Faculty members 
Course objectiveSuccessful students are expected to know application of time domain and frequency domain signal processing methods in Matlab, Labview or similar environment.  
Learning outcomes
  1. A student completing the course successfully will L.O.1. Recognize basic signal processing problems,
  2. L.O.2. Model encountered problems,
  3. L.O.3. Know which algorithms can be used to solve the problem, know the advantages and disadvantages of these algorithms, and implement them by writing programs,
  4. L.O.4. Apply the techniques and algorithms learnt in the class to problems encountered in projects ,
  5. L.O.5. Have adequate knowledge to follow and understand other signal processing algorithms.
Course ContentSampling, 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.  
References1. Oppenheim , A.V. and R.W. Schafer, Discrete-time Signal Processing, .Pearson, 2010.
2. Lecture Notes.
 

Course outline weekly

WeeksTopics
Week 1
Week 2DFT , Upsampling, Downsampling
Week 3
Week 4Analysis of Discrete-Time Systems
Week 5
Week 6Effect of Quantization and Phase Shift
Week 7
Week 8IIR Filter Design
Week 9
Week 10Windowing and FIR Filter Design
Week 11
Week 12Discrete-Time Filtering using DFT
Week 13
Week 14Image Processing
Week 15Preparation for Final exam
Week 16Final Exam

Assesment methods

Course activitiesNumberPercentage
Attendance00
Laboratory750
Application00
Field activities00
Specific practical training00
Assignments00
Presentation00
Project00
Seminar00
Midterms00
Final exam150
Total100
Percentage of semester activities contributing grade succes050
Percentage of final exam contributing grade succes050
Total100

Workload and ECTS calculation

Activities Number Duration (hour) Total Work Load
Course Duration (x14) 0 0 0
Laboratory 7 3 21
Application000
Specific practical training000
Field activities000
Study Hours Out of Class (Preliminary work, reinforcement, ect)7428
Presentation / Seminar Preparation000
Project000
Homework assignment000
Midterms (Study duration)000
Final Exam (Study duration) 11212
Total Workload151952

Matrix Of The Course Learning Outcomes Versus Program Outcomes

D.9. Key Learning OutcomesContrubition level*
12345
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

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