EEE 301 | Course Introduction and Application Information

Course Name
Signal Processing and Linear Systems
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
EEE 301
Fall
3
2
4
7

Prerequisites
  MATH 153 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Required
Course Level
First Cycle
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives The purpose of this course is to provide students with the mathematical foundations and tools for analysis of signals processed by systems. This is a first step to understand how signals carry information and how systems process this information, which will be necessary for subsequent courses in the overall ETE program.
Learning Outcomes The students who succeeded in this course;
  • Describe different types of signals, signal representations, and main properties of signals useful to their analysis,
  • describe the fundamental properties of linear systems,
  • determine system characteristics such as linearity, time-invariance, causality and stability,
  • describe the basic concepts of Fourier series and Fourier transforms for discrete- and continuous-time signals,
  • use transform analysis and convolution to analyze behavior of linear, time-invariant systems,
  • explain how to obtain an LTI system response to standard signals (impulse response, step response), and then to any signal in terms of those,
  • perform the Laplace and z transforms and corresponding inverse transforms using the definitions, tables of standard transforms and properties, and partial fraction expansion,
  • use Matlab signal processing toolbox and Simulink software to create, analyze and process signals, and to simulate and analyze systems.
Course Content Topics covered in class include timedomain analysis of continuoustime and discretetime systems; Fourier series and periodic signals; Fourier transforms; sampling and discrete Fourier transforms; Discretetime signals and systems, Ztransforms.

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Signals and systems; introduction and mathematical preliminaries; Some examples of signals and systems Chapter 1. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
2 Signal classification and energy; basic operations with signals; classification of systems; basic system properties Chapter 1. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
3 LTI systems and the impulse response; convolution sum representation of DT LTI systems; examples and properties of DT LTI systems Chapter 2. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
4 Continuous time LTI systems; convolution integral representation; properties and examples; singularity functions Chapter 2. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
5 Fourier series representation of continuoustime periodic signals; convergence and Gibbs’ phenomenon; properties of CT FS Chapter 3. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
6 Discrete time Fourier series; properties of DT FS; Fourier series and LTI systems; frequency response and filtering; examples Chapter 3. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
7 Review for Midterm; motivation of the Fourier transform Chapter 3. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
8 The continuous time Fourier transform; Fourier transforms of periodic signals; properties of the CT Fourier transform; the convolution and multiplication properties with examples Chapter 4. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
9 The discrete time Fourier transform; DT Fourier transform properties and examples; duality in Fourier series and Fourier transform Chapter 5. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
10 The magnitude phase representation of the Fourier transform; frequency response of LTI systems; Bode plots; CT & DT rational frequency responses Chapter 6. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
11 The sampling theorem; sampling of bandlimited continuous time signals; analysis of sampling in frequency and time domains; undersampling and aliasing Chapter 7. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
12 Discrete time processing of continuous time signals; sampling of discretetime signals; DT decimation and interpolation Chapter 7. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
13 The Laplace transform; its inverse and properties; system functions of LTI systems; block diagram representations for causal LTI systems with rational system functions Chapter 9. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
14 The z transform; its inverse and properties; analysis and characterization of DT LTI systems using z transforms; system function algebra and block diagrams Chapter 10. Signals & Systems. Oppenheim & Willsky. ISBN 0136511759.
15 Selected signal processing applications; review for Final Lecture Notes
16 Review of the Semester  

 

Course Textbooks A. V. Oppenheim, A. S. Willsky, with H. Nawab, Signals & Systems, Prentice Hall, 1997, 2nd Ed., ISBN: 0136511759.
References 1) B.P. Lathi, Signal Processing and Linear Systems, Oxford University Press, 1998. 2) S. Haykin and B. Van Veen, Signals and Systems, Wiley, 1999.

 

EVALUATION SYSTEM

Semester Requirements Number Percentage
Participation
Laboratory / Application
8
20
Field Work
Quizzes / Studio Critiques
-
-
Homework / Assignments
-
-
Presentation / Jury
Project
Seminar / Workshop
Portfolios
Midterms / Oral Exams
2
40
Final / Oral Exam
1
40
Total

Contribution of Semester Work to Final Grade
10
60
Contribution of Final Work to Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Activities Number Duration (Hours) Workload
Course Hours
Including exam week: 16 x total hours
16
3
48
Laboratory / Application Hours
Including exam week: 16 x total hours
16
2
Study Hours Out of Class
15
7
Field Work
Quizzes / Studio Critiques
-
-
Homework / Assignments
-
-
Presentation / Jury
Project
Seminar / Workshop
Portfolios
Midterms / Oral Exams
2
19
Final / Oral Exam
1
28
    Total
251

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Qualifications / Outcomes
* Level of Contribution
1
2
3
4
5
1

To have sufficient background in Mathematics, Basic sciences and Biomedical Engineering areas and the skill to use this theoretical and practical background in the problems of the Biomedical Engineering.

2

To identify, formulate and solve Biomedical Engineering-related problems by using state-of-the-art methods, techniques and equipment; to select and apply appropriate analysis and modeling methods for this purpose.

3

To analyze a complex system, system components or process, and to design with realistic limitations to meet the requirements using modern design techniques; to apply modern design techniques for this purpose.

4

To choose and use the required modern techniques and tools for analysis and solution of complex problems in Biomedical Engineering applications; to skillfully use information technologies.

5

To design and do simulation and/or experiment, collect and analyze data and interpret results for studying complex engineering problems or research topics of the discipline. 

6

To efficiently participate in intradisciplinary and multidisciplinary teams; to work independently.

7

To communicate both in oral and written form in Turkish; to have knowledge of at least one foreign language; to have the skill to write and understand reports, prepare design and production reports, present, give and receive clear instructions.

8

To recognize the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.

9

To behave ethically, to be aware of professional and ethical responsibilities; to have knowledge about the standards in Biomedical Engineering applications.

10

To have information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.

11

To have knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of Biomedical Engineering solutions.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest