EE 302 Digital Signal ProcessingMEF UniversityDegree Programs Computer EngineeringGeneral Information For StudentsDiploma SupplementErasmus Policy Statement
Computer Engineering
Bachelor Length of the Programme: 4 Number of Credits: 240 TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF: Level 6

Ders Genel Tanıtım Bilgileri

School/Faculty/Institute Faculty of Engineering
Course Code EE 302
Course Title in English Digital Signal Processing
Course Title in Turkish Sayısal İşaret İşleme
Language of Instruction EN
Type of Course Flipped Classroom
Level of Course Introductory
Semester Spring
Contact Hours per Week
Lecture: 3 Recitation: None Lab: 1 Other: None
Estimated Student Workload hours per semester
Number of Credits 6 ECTS
Grading Mode Standard Letter Grade
Pre-requisites EE 204 - Signals and Systems
Expected Prior Knowledge Prior knowledge in continuous and discrete time signals and systems, Fourier series and Fourier transform, properties of discrete-time signals and systems, convolution.
Co-requisites None
Registration Restrictions Only Undergraduate Students
Overall Educational Objective To learn the analysis of discrete time signals and systems.
Course Description This course provides a comprehensive introduction to digital signal processing and time-scale analysis. The following topics are covered: discrete time signals in the time domain, linear time-invariant systems, convolution, frequency domain representation of discrete signals and systems, Discrete Time Fourier Transform (DTFT), sampling theory, discrete-time processing of analog signals, z-transform, transform analysis of systems, stability and causality, Discrete Fourier Transform (DFT), circular convolution, Fast Fourier Transform (FFT), implementation of and structures for discrete systems, digital filters: specifications, FIR filter theory and design methods, IIR filter theory and design methods.
Course Description in Turkish Bu derste sayısal işaret işlemenin ve zaman-ölçek analizinin temel kavramları şu konu başlıkları altında kapsamlı bir şekilde incelenmektedir: ayrık zamanlı işaretler, lineer zamanla-değişmeyen sistemler, konvolusyon, sayısal işaretler ve sistemlerin frekans bölgesi gösterimleri, Ayrık Zamanlı Fourier Dönüşümü (AZFD), örnekleme teorisi, analog işaretlerin ayrık-zamanlı işlenmesi, z-dönüşümü, sistemlerin dönüşüm analizi, kararlılık ve nedensellik, Ayrık Fourier Dönüşümü (AFD), dairesel konvolüsyon, Hızlı Fourier Dönüşümü (HFD), ayrık zamanlı sistemlerin yapısı ve gerçeklenmesi, sayısal süzgeçler: tanımlamalar, FIR süzgeç teorisi ve tasarım yöntemleri, IIR süzgeç teorisi ve tasarım yöntemleri.

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to:
1) explain the basic concepts of signals, signal processing and digital signals;
2) analyze the signals and systems in time and frequency domain;
3) analyze discrete-time signals and systems in transfer domain;
4) use MATLAB to analyse and design discrete-time systems;
5) carry out a digital signal processing project and draw conclusions;
6) demonstrate team effort during a project;
7) prepare technical reports and present to a range of audiences.
Program Learning Outcomes/Course Learning Outcomes 1 2 3 4 5 6 7
1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics
2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors
3) An ability to communicate effectively with a range of audiences
4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts
5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives
6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions
7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.

Relation to Program Outcomes and Competences

N None S Supportive H Highly Related
     
Program Outcomes and Competences Level Assessed by
1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics H Exam
2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors N
3) An ability to communicate effectively with a range of audiences H Project
4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts N
5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives H Project
6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions H Lab,Project
7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. N
Prepared by and Date SERAP KIRBIZ , April 2018
Course Coordinator SERAP KIRBIZ
Semester Spring
Name of Instructor Asst. Prof. Dr. SERAP KIRBIZ

Course Contents

Week Subject
1) Discrete-time signals and systems (2.1-2.5)
2) Frequency domain representation of discrete signals and systems. (2.6-2.9)
3) Sampling theory, Discrete-time processing of analog signals (4.1-4.3)
4) Discrete Fourier Series (DFS) (8.1-8.4)
5) Discrete Fourier Transform (DFT), Circular convolution (8.5-8.7)
6) z-transform (3.1-3.2)
7) z-transform (3.3-3.4)
8) Transform analysis of Linear Time Invariant Systems (5.1-5.3)
9) Stability and causality (5.4-5.6)
10) Structures for Discrete-Time Systems (6.1-6.5)
11) Digital filters: specifications. FIR filter theory and design methods (7.1-7.2)
12) FIR filter theory and design methods (7.3)
13) IIR filter theory and design methods (7.4-7.5)
14) Fast Fourier Transform (FFT) (9.1-9.3)
15) Final Exam/Project/Presentation Period
16) Final Exam/Project/Presentation Period
Required/Recommended Readings1. “Discrete-Time Signal Processing”, Oppenheim and Schafer, Prentice-Hall, 3rd edition, 2010 (Textbook) 2. “Digital Signal Processing, Principles, Algorithms and Applications”, Proakis and Manolakis, Prentice-Hall, 2007.
Teaching MethodsContact hours using “Flipped Classroom” as an active learning technique
Homework and ProjectsProblems from textbook (they will not be collected and not graded, quiz questions will be very similar or identical to the problems). 1 Project
Laboratory Work7 laboratories on analyzing signals in time and frequency domains and designing discrete time systems.
Computer UseStudents will use MATLAB in lab and to implement discrete time systems for their projects.
Other ActivitiesNone
Assessment Methods
Assessment Tools Count Weight
Laboratory 7 % 12
Quiz(zes) 2 % 8
Project 1 % 30
Midterm(s) 2 % 50
TOTAL % 100
Course Administration

Instructor’s office: 5th Floor office hours: Tue 16:00-17:00, Thu 16:00-17:00 email address: kirbizs@mef.edu.tr Rules for attendance: YÖK Regulations. Missing a quiz: Provided that proper documents of excuse are presented, each missed quiz by the student will be given a grade which is equal to the average of all of the other quizzes. No make-up will be given. Missing a midterm: Provided that proper documents of excuse are presented, each missed midterm by the student will be given the grade of the final exam. No make-up will be given. Eligibility to take the final exam: Students are required to collect a weighted average of at least 25 points from midterm exam, quizzes, laboratory and projects to be able to take the final exam. Missing a final: Faculty regulations. A reminder of proper classroom behavior, code of student conduct: YÖK Regulations Statement on plagiarism: YÖK Regulations http://3fcampus.mef.edu.tr/uploads/cms/webadmin.mef.edu.tr/4833_2.pdf