FACULTY OF ENGINEERING

Department of Biomedical Engineering

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/Spring
3
2
4
7

Prerequisites
  MATH 153 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Service Course
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course -
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,
  • Define the fundamental properties of linear systems,
  • Identify system characteristics such as linearity, time-invariance, causality and stability,
  • Tell the basic concepts of Fourier series and Fourier transforms for discrete- and continuous-time signals,
  • Analyze behavior of linear, time-invariant systems by using transform analysis and convolution,
  • Explain the response of LTI systems to standard signals (impulse response, step response), and then to any signal in terms of those standard signals,
  • Formulate the Laplace and Z transforms and corresponding inverse transforms using the definitions, tables of standard transforms and properties, and partial fraction expansion,
  • Simulate signals and systems using Matlab signal processing toolbox and Simulink.
Course Description 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 Notes/Textbooks

L. F. Chaparro, A. Akan, Signals and Systems using MATLAB, Academic Press, 2019, 3rd Ed., ISBN: 9780128142042.

Suggested Readings/Materials

A. V. Oppenheim, A. S. Willsky, with H. Nawab, Signals & Systems, Prentice Hall, 1997, 2nd Ed., ISBN: 9780138147570.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
1
30
Field Work
Quizzes / Studio Critiques
-
-
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exams
Midterm
1
30
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
2
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
2
32
Study Hours Out of Class
16
4
64
Field Work
0
Quizzes / Studio Critiques
-
-
0
Portfolio
0
Homework / Assignments
-
0
Presentation / Jury
0
Project
0
Seminar / Workshop
0
Oral Exam
0
Midterms
1
30
30
Final Exam
1
36
36
    Total
210

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

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

To have adequate knowledge in Mathematics, Science and Biomedical Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

X
2

To be able to identify, define, formulate, and solve complex Biomedical Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

X
4

To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Biomedical Engineering applications.

X
5

To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Biomedical Engineering research topics.

X
6

To be able to work efficiently in Biomedical Engineering disciplinary and multi-disciplinary teams; to be able to work individually.

X
7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions.

8

To have knowledge about global and social impact of Biomedical Engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of engineering solutions.

X
9

To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications.

X
10

To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

X
11

To be able to collect data in the area of Biomedical Engineering, and to be able to communicate with colleagues in a foreign language.

X
12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Biomedical Engineering.

X

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

 


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