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 |
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Estimated Student Workload |
150 hours per semester |
Number of Credits |
6 ECTS |
Grading Mode |
Standard Letter Grade
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Pre-requisites |
EE 204 - Signals and Systems
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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.
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Program Learning Outcomes/Course Learning Outcomes |
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1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. |
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2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. |
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3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. |
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4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. |
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5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. |
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6) Internalization and dissemination of professional ethical standards. |
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7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. |
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8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). |
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9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity. |
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10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. |
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11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. |
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12) Ability to acquire knowledge independently, and to plan one’s own learning. |
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13) Demonstration of advanced competence in the clarity and composition of written work and presentations. |
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Relation to Program Outcomes and Competences
N None |
S Supportive |
H Highly Related |
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Program Outcomes and Competences |
Level |
Assessed by |
1) |
Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. |
N |
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2) |
Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. |
N |
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3) |
Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. |
H |
Exam,HW,Participation
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4) |
Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. |
N |
|
5) |
Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. |
N |
|
6) |
Internalization and dissemination of professional ethical standards. |
N |
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7) |
Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. |
N |
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8) |
Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). |
N |
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9) |
Recognition, understanding, and respect for the complexity of sociocultural and international diversity. |
S |
Participation
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10) |
Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. |
S |
HW,Participation
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11) |
Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. |
N |
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12) |
Ability to acquire knowledge independently, and to plan one’s own learning. |
S |
Exam,HW
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13) |
Demonstration of advanced competence in the clarity and composition of written work and presentations. |
H |
Exam,HW
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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 Readings | 1. “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.
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Teaching Methods | Contact hours using “Flipped Classroom” as an active learning technique |
Homework and Projects | Problems from textbook (they will not be collected and not graded, quiz questions will be very
similar or identical to the problems).
1 Project
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Laboratory Work | 7 laboratories on analyzing signals in time and frequency domains and designing discrete time systems. |
Computer Use | Students will use MATLAB in lab and to implement discrete time systems for their projects. |
Other Activities | None |
Assessment Methods |
Assessment Tools |
Count |
Weight |
Laboratory |
7 |
% 12 |
Quiz(zes) |
2 |
% 8 |
Project |
1 |
% 30 |
Midterm(s) |
2 |
% 50 |
TOTAL |
% 100 |
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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
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