ECTS - Digital Signal Processing

Digital Signal Processing (CMPE463) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Digital Signal Processing CMPE463 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives The objective of this course is to introduce basic concepts and different approaches Digital Signal Processing. To introduce students to a working and hands-on knowledge of digital signal processing algorithms and filters.
Course Learning Outcomes The students who succeeded in this course;
  • Design and implement digital signal processing algorithms and filters for a given problem.
  • Decide on and apply suitable digital signal processing technique(s) to a given problem.
Course Content Discrete-time domain and frequency domain representation of signals and systems; sampling and reconstruction; DFT, FFT, z - transform, filter design techniques; finite word length effects; 2-D filtering; applications of DSP; programming of some DSP processors.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction : Signals , Systems and Signal Processing; Classification and Representation of Signals in discrete time domain; Linear, Time-Invariant Systems Chapters 1-2 (main text)
2 Difference Equations; Frequency Response Ch 1-2
3 Sampling and Reconstruction The discrete Fourier transform. ( DFT ) Ch 9
4 Sampling and Reconstruction The discrete Fourier transform. ( DFT ) Ch 9
5 Fast Fourier transform. ( FFT ) z- transform Frequency and time-domain response of filters. Ch 3-8
6 Fast Fourier transform. ( FFT ) z- transform Frequency and time-domain response of filters. Ch.3-8
7 Fast Fourier transform. ( FFT ) z- transform Frequency and time-domain response of filters. Ch 3-8
8 Fast Fourier transform. ( FFT ) z- transform Frequency and time-domain response of filters. Ch 3-8
9 Digital filter design, FIR and IIR filters. Digital filter structures. Finite word length effects. Chapter 8-9-10 (From other sources 1)
10 Digital filter design, FIR and IIR filters. Digital filter structures. Finite word length effects. Chapter 8-9-10 (From other sources 1)
11 Digital filter design, FIR and IIR filters. Digital filter structures. Finite word length effects. Chapter 8-9-10 (From other sources 1)
12 2- Dimensional Filtering Applications of DSP DSP Processors Chapter 15 (From other sources 1)
13 2- Dimensional Filtering Applications of DSP DSP Processors Chapter 15 (From other sources 1)
14 2- Dimensional Filtering Applications of DSP DSP Processors Chapter 15 (From other sources 1)

Sources

Course Book 1. John G. Prokis and Dimitris G. Manolakis, “Digital Signal Processing : Principle, Algorithms and Applications” Prentice Hall Inc., Englewood Cliffs, NJ (USA), 3rd Ed., 1996.
Other Sources 2. 1. S. K. Mitra, “Digital Signal Processing : A Computer-Based Approach” Mc Graw Hill Co. Inc., NY (USA), 1998.
3. 2. P. Lapsley, J. Bier and E.A. Lee ‘’ DSP Processor Fundamentals : Architectures and Features ‘’ IEEE Press, New York( USA ), 1997
4. 3. Lawrence R. Rabiner and Bernard Gold “Theory and Application of Digital Signal Processing” Prentice Hall, NJ (USA), 1975.
5. 4. C. Sidney Burrus, Computer-Based Exercises for Signal Processing Using Matlab, Prentice Hall, 1994. Matlab for Students, Prentice Hall, 1994. (for various formats).
6. 5. R.G.Lyons, “Understanding Digital Signal Processing (2nd Edition)”, Prentice-Hall, 2004.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 2 20
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 40
Final Exam/Final Jury 1 40
Toplam 5 100
Percentage of Semester Work 60
Percentage of Final Work 40
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Gain sufficient knowledge in mathematics, science and computing; be able to use theoretical and applied knowledge in these areas to solve engineering problems related to information systems.
2 To be able to identify, define, formulate and solve complex engineering problems; to be able to select and apply appropriate analysis and modeling methods for this purpose.
3 Designs a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; applies modern design methods for this purpose.
4 To be able to develop, select and use modern techniques and tools required for the analysis and solution of complex problems encountered in information systems engineering applications; to be able to use information technologies effectively. X
5 Designs and conducts experiments, collects data, analyzes and interprets results to investigate complex engineering problems or research topics specific to the discipline of information systems engineering. X
6 Can work effectively in disciplinary and multidisciplinary teams; can work individually.
7 a. Communicates effectively both orally and in writing; writes effective reports and understands written reports, prepares design and production reports, makes effective presentations, gives and receives clear and understandable instructions. b. Knows at least one foreign language.
8 To be aware of the necessity of lifelong learning; to be able to access information, to be able to follow developments in science and technology and to be able to renew himself/herself continuously.
9 a. Acts in accordance with the principles of ethics, gains awareness of professional and ethical responsibility. b. Gains knowledge about the standards used in information systems engineering applications.
10 a. Gains knowledge about business life practices such as project management, risk management and change management. b. Gains awareness about entrepreneurship and innovation. c. Gains knowledge about sustainable development.
11 a. To be able to acquire knowledge about the universal and social effects of information systems engineering applications on health, environment and safety and the problems of the era reflected in the field of engineering. b. Gains awareness of the legal consequences of engineering solutions.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 14 2 28
Presentation/Seminar Prepration
Project
Report
Homework Assignments 2 5 10
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 2 10 20
Prepration of Final Exams/Final Jury 1 20 20
Total Workload 126