ECTS - Digital Signal Processing
Digital Signal Processing (CMPE463) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Digital Signal Processing | CMPE463 | Area Elective | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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N/A |
Course Language | English |
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Course Type | Technical Elective Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture. |
Course Lecturer(s) |
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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;
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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 |
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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. |
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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 |
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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 |
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Percentage of Final Work | 40 |
Total | 100 |
Course Category
Core Courses | |
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Major Area Courses | |
Supportive Courses | X |
Media and Managment Skills Courses | |
Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
# | Program Qualifications / Competencies | Level of Contribution | ||||
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1 | 2 | 3 | 4 | 5 | ||
1 | Adequate knowledge in mathematics, science and subjects specific to the software engineering discipline; the ability to apply theoretical and practical knowledge of these areas to complex engineering problems. | X | ||||
2 | The ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. | X | ||||
3 | The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. | |||||
4 | The ability to develop, select and utilize modern techniques and tools essential for the analysis and determination of complex problems in software engineering applications; the ability to utilize information technologies effectively. | X | ||||
5 | The ability to gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the software engineering discipline. | |||||
6 | The ability to work effectively in inter/inner disciplinary teams; ability to work individually. | |||||
7 | Effective oral and written communication skills in Turkish; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. | |||||
8 | The knowledge of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. | |||||
9 | Recognition of the need for lifelong learning; the ability to access information and follow recent developments in science and technology with continuous self-development | |||||
10 | The ability to behave according to ethical principles, awareness of professional and ethical responsibility. | |||||
11 | Knowledge of the standards utilized in software engineering applications. | |||||
12 | Knowledge on business practices such as project management, risk management and change management. | |||||
13 | Awareness about entrepreneurship, and innovation. | |||||
14 | Knowledge on sustainable development. | |||||
15 | Knowledge of the effects of software engineering applications on the universal and social dimensions of health, environment, and safety. | |||||
16 | Awareness of the legal consequences of engineering solutions. | |||||
17 | An ability to apply algorithmic principles, mathematical foundations, and computer science theory in the modeling and design of computer-based systems with the trade-offs involved in design choices. | X | ||||
18 | The ability to apply engineering approach to the development of software systems by analyzing, designing, implementing, verifying, validating and maintaining software systems. |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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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 |