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
Real Time Signal Processing EE426 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
EE306
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, Demonstration, Experiment, Drill and Practice, Team/Group, Project Design/Management.
Course Coordinator
Course Lecturer(s)
Course Assistants
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;
  • Describe the architecture and basic operation of fixed-point and foating-point DSPs
  • Perform worst-case timing analysis on real-time DSP systems
  • Develop and realize computationally effcient algorithms on the DSP platform (e.g. FFT, fast convolution)
  • Optimize DSP code (e.g. software pipelining)
  • Draw block diagrams of FIR and IIR filters under various realization structures and describe the advantages and disadvantages of each realization structure
  • Realize real-time FIR and IIR filter designs on the DSP platform, compare experimental results to theoretical expectations, and identify the source of performance discrepancies
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
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

Evaluation System

Requirements Number Percentage of Grade
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
Percentage of Final Work 30
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 Accumulated knowledge on mathematics, science and mechatronics engineering; an ability to apply the theoretical and applied knowledge of mathematics, science and mechatronics engineering to model and analyze mechatronics engineering problems.
2 An ability to differentiate, identify, formulate, and solve complex engineering problems; an ability to select and implement proper analysis, modeling and implementation techniques for the identified engineering problems.
3 An ability to design a complex system, product, component or process to meet the requirements under realistic constraints and conditions; an ability to apply contemporary design methodologies; an 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 An ability to develop, select and use modern techniques, skills and tools for application of mechatronics engineering and robot technologies; an ability to use information and communications technologies effectively.
5 An ability to design experiments, perform experiments, collect and analyze data and assess the results for investigated problems on mechatronics engineering and robot technologies.
6 An ability to work effectively on single disciplinary and multi-disciplinary teams; an 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.
7 An ability to express creative and original concepts and ideas effectively in Turkish and English language, oral and written, and technical drawings.
8 An 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 A 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, societal 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.
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 planing, improving or changing the norms with a criticism.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
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