| 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 |
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| Estimated Student Workload | 150 hours per semester | ||||||
| Number of Credits | 6 ECTS | ||||||
| Grading Mode | Standard Letter Grade | ||||||
| Pre-requisites |
EE 204 - Signals and Systems |
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| Co-requisites | None | ||||||
| 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. | ||||||
| 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 Learning Outcomes and CompetencesUpon 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) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | |||||||
| 2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | |||||||
| 3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | |||||||
| 4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | |||||||
| 5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | |||||||
| 6) Internalization and dissemination of professional ethical standards. | |||||||
| 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. | |||||||
| 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). | |||||||
| 9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | |||||||
| 10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | |||||||
| 11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | |||||||
| 12) Ability to acquire knowledge independently, and to plan one’s own learning. | |||||||
| 13) Demonstration of advanced competence in the clarity and composition of written work and presentations. |
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | N | |
| 2) | Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | N | |
| 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 |
| 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 | |
| 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 | |
| 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 | |
| 9) | Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | S | Participation |
| 10) | Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | S | HW,Participation |
| 11) | Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | N | |
| 12) | Ability to acquire knowledge independently, and to plan one’s own learning. | S | Exam,HW |
| 13) | Demonstration of advanced competence in the clarity and composition of written work and presentations. | H | Exam,HW |
| Prepared by and Date | SERAP KIRBIZ , April 2018 |
| Course Coordinator | SERAP KIRBIZ |
| Semester | Spring |
| Name of Instructor | Asst. Prof. Dr. SERAP KIRBIZ |
| 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. | ||||||||||||||||||
| 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 | ||||||||||||||||||
| 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 |
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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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| Activity | No/Weeks | Hours | Calculation | ||||
| No/Weeks per Semester | Preparing for the Activity | Spent in the Activity Itself | Completing the Activity Requirements | ||||
| Course Hours | 14 | 2 | 3 | 70 | |||
| Laboratory | 7 | 1 | 1 | 1 | 21 | ||
| Project | 1 | 20 | 1 | 1 | 22 | ||
| Midterm(s) | 2 | 10 | 2 | 24 | |||
| Final Examination | 1 | 11 | 2 | 13 | |||
| Total Workload | 150 | ||||||
| Total Workload/25 | 6.0 | ||||||
| ECTS | 6 | ||||||