ECTS - Real Time Signal Processing
Real Time Signal Processing (EE426) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Real Time Signal Processing | EE426 | Area Elective | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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EE306 |
Course Language | English |
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Course Type | Elective Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture, Demonstration, Experiment, Drill and Practice, Team/Group, Project Design/Management. |
Course Lecturer(s) |
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Course Objectives | This course provides an introduction to the principles of real-time digital signal processing (DSP).The focus of this course is hands-on development of real-time signal processing algorithms using audio-based DSP kits in a laboratory environment |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Architecture, instruction set, and hardware and software development tools associated with the Texas Instruments TMS320C6x family of fixed and floating processors. Signal processing applications such as waveform generation, FIR and IIR digital filtering, and DFT and FFT based spectral analysis and filtering. Requires an extensive DSP project of the |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Course introduction, Introduction to the C6000 DSK, Code Composer Studio IDE, Matlab, and basic skills | Glance at lecture notes |
2 | Sampling, quantization, and working with the AIC23 codec | Review last week and Glance this week’s topics from the lecture |
3 | DSP basics, memory architecture, I/O, and interrupt data processing | Review last week and Glance this week’s topics from the lecture |
4 | Review of FIR filtering. FIR fillter design techniques and tools | Review last week and Glance this week’s topics from the lecture |
5 | FIR fillter realization structures and practical considerations | Review last week and Glance this week’s topics from the lecture |
6 | Review of IIR filtering. IIR filter design techniques and tools | Review last week and Glance this week’s topics from the lecture |
7 | IIR filter realization structures and practical considerations | Review last week and Glance this week’s topics from the lecture |
8 | Writing effcient code: optimizing compiler, effect of data types and memory map | Review last week and Glance this week’s topics from the lecture |
9 | Fetch and execute packets, pipelining. Assembly language programming | Review last week and Glance this week’s topics from the lecture |
10 | Assembly language programming(cont’d) and code optimization | Review last week and Glance this week’s topics from the lecture |
11 | Computation of the Fast Fourier Transform. (FFT) | Review last week and Glance this week’s topics from the lecture |
12 | Applications of the FFT | Review last week and Glance this week’s topics from the lecture |
13 | Adaptive filtering basics. The Least Mean Squares algorithm | Review last week and Glance this week’s topics from the lecture |
14 | Other applications of DSP and review | Review last week and Glance this week’s topics from the lecture |
15 | Final Examination Period | Review of topics |
16 | Final Examination Period | Review of topics |
Sources
Course Book | 1. Real-Time Digital Signal Processing: Based on the TMS320C6000, Nasser Kehtarnavaz |
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Evaluation System
Requirements | Number | Percentage of Grade |
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Attendance/Participation | - | - |
Laboratory | 10 | 20 |
Application | 1 | 20 |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | - | - |
Presentation | - | - |
Project | - | - |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 2 | 30 |
Final Exam/Final Jury | 1 | 30 |
Toplam | 14 | 100 |
Percentage of Semester Work | 70 |
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Percentage of Final Work | 30 |
Total | 100 |
Course Category
Core Courses | X |
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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 | ||||
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1 | 2 | 3 | 4 | 5 | ||
1 | Accumulated knowledge on mathematics, science and mechatronics engineering; ability to apply the theoretical and applied knowledge to model and analyze mechatronics engineering problems. | |||||
2 | Ability to identify, define and formulate problems related to the field and to select and apply appropriate analysis and modeling methods to solve these problems. | |||||
3 | Ability to design a complex system, product, component or process to meet the requirements under realistic constraints and conditions; ability to apply contemporary design methodologies; ability to implement effective engineering creativity techniques in mechatronics engineering. (Realistic constraints and conditions may include economics, environment, sustainability, producibility, ethics, human health, social and political problems.) | |||||
4 | Ability to develop, select and use modern techniques, skills and tools for application of mechatronics engineering and robot technologies; ability to use information and communications technologies effectively. | |||||
5 | Ability to design and perform experiments, collect and analyze data and assess the results for investigated problems on mechatronics engineering and robot technologies. | |||||
6 | Ability to work effectively on intra-disciplinary and multi-disciplinary teams; ability for individual work; ability to communicate and collaborate/cooperate effectively with other disciplines and scientific/engineering domains or working areas, ability to work with other disciplines including electrical & electronics and computer engineering. | |||||
7 | Ability to express creative and original concepts and ideas effectively in Turkish and English language, oral and written, and technical drawings. | |||||
8 | Ability to reach information on different subjects required by the wide spectrum of applications of mechatronics engineering, criticize, assess and improve the knowledge-base; consciousness on the necessity of improvement and sustainability as a result of life-long learning; monitoring the developments on science and technology; awareness on entrepreneurship, innovative and sustainable development and ability for continuous renovation. | |||||
9 | Consciousness on professional and ethical responsibility, competency on improving professional consciousness and contributing to the improvement of profession itself. | |||||
10 | Knowledge on the applications at business life such as project management, risk management and change management and competency on planning, managing and leadership activities on the development of capabilities of workers who are under his/her responsibility working around a project. | |||||
11 | Knowledge about the global, social and individual effects of mechatronics engineering applications on the human health, environment and security and cultural values and problems of the era; consciousness on these issues; awareness of legal results of engineering solutions. | |||||
12 | Competency on defining, analyzing and surveying databases and other sources, proposing solutions based on research work and scientific results and communicate and publish numerical and conceptual solutions in the field of mechatronics engineering. | |||||
13 | Consciousness on the environment and social responsibility, competencies on observation, improvement and modify and implementation of projects for the society and social relations and be an individual within the society in such a way that planning, improving or changing the norms with a criticism. |
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 | 4 | 3 | 12 |
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | 14 | 3 | 42 |
Presentation/Seminar Prepration | |||
Project | |||
Report | |||
Homework Assignments | 4 | 3 | 12 |
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 2 | 4 | 8 |
Prepration of Final Exams/Final Jury | 1 | 5 | 5 |
Total Workload | 127 |