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 Adequate knowledge of subjects related to mathematics, natural sciences, and Electrical and Electronics Engineering discipline; ability to apply theoretical and applied knowledge in those fields to the solution of complex engineering problems. X
2 An ability to identify, formulate, and solve complex engineering problems, ability to choose and apply appropriate models and analysis methods for this. X
3 An ability to design a system, component, or process under realistic constraints to meet desired needs, and ability to apply modern design approaches for this. X
4 The ability to select and use the necessary modern techniques and tools for the analysis and solution of complex problems encountered in engineering applications; the ability to use information technologies effectively X
5 Ability to design and conduct experiments, collect data, analyze and interpret results for investigating complex engineering problems or discipline-specific research topics. X
6 An ability to function on multi-disciplinary teams, and ability of individual working. X
7 Ability to communicate effectively orally and in writing; knowledge of at least one foreign language; active report writing and understanding written reports, preparing design and production reports, the ability to make effective presentation the ability to give and receive clear and understandable instructions. X
8 Awareness of the necessity of lifelong learning; the ability to access knowledge, follow the developments in science and technology and continuously stay updated. X
9 Acting compliant with ethical principles, professional and ethical responsibility, and knowledge of standards used in engineering applications. X
10 Knowledge about professional activities in business, such as project management, risk management, and change management awareness of entrepreneurship and innovation; knowledge about sustainable development. X
11 Knowledge about the impacts of engineering practices in universal and societal dimensions on health, environment, and safety. the problems of the current age reflected in the field of engineering; awareness of the legal consequences of engineering solutions. X

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