Mechatronics Engineering (English)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

General course introduction information

Course Code:

EEE311

Course Name:

Digital Signal Processing

Course Semester:

Fall

Course Credits:

Theoretical	Practical	Credit	ECTS
2	2	3	5

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Compulsory

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr.Öğr.Üyesi MAHSA MIKAEILI

Course Lecturer(s):

Dr.Öğr.Üyesi MAHSA MIKAEILI

Course Assistants:

Course Objective and Content

Course Objectives:	To introduce the fundamental principles of discrete time and quantized signal processing so that students may analyze and design digital signal processing systems.
Course Content:	Discrete time signals and systems, properties of linear time invariant systems, the z transform, Fourier representation of signals, transform analysis of LTI systems, sampling of continuous time signals, discrete fourier transform, computing the discrete Fourier transform, design of FIR filters, design of IIR filters, multirate signal processing, finite wordlength effects.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
2 - Skills
Cognitive - Practical
1) Analyze the effect of sampling and quantization on a signal or system.
2) Analyze discrete time systems in the time and spectral domains.
3) Design and implement digital systems for typical signal processing applications.
4) Implement digital signal processing algorithms using MATLAB.
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	Introduction to Digital Signal Processing, Discrete time signals and systems
2)	Properties of Linear Time Invariant Systems
3)	The z transform
4)	The inverse z transform
5)	Fourier representation of discrete time signals
6)	Transform Analysis of LTI Systems
7)	Sampling of continuous time signals
8)	Discrete Fourier Transform
9)	Computing the Discrete Fourier Transform
10)	Design of FIR Filters
11)	Design of IIR Filters
12)	Multirate Signal Processing
13)	Finite wordlength effects
14)	Various applications.

Sources

Course Notes / Textbooks:	Alan Oppenheim, Ronald Schafer, John Buck, “Discrete-Time Signal Processing,” Prentice Hall, 2nd Edition.
References:	Yok

Course-Program Learning Outcome Relationship

Learning Outcomes	1	2	3	4
Program Outcomes
1) A solid foundation in mathematics, natural sciences, and mechatronics engineering; the ability to apply both theoretical and practical knowledge in these fields to model and solve complex engineering problems.
2) The ability to identify, define, formulate, and solve complex mechatronics engineering problems; and to select and apply appropriate analysis and modeling methods for this purpose.
3) The ability to design complex mechatronics engineering systems, processes, devices, or products to meet specified requirements under realistic constraints and conditions; and to apply modern design methodologies for this purpose. (Realistic constraints and conditions may include economic, environmental, sustainability, manufacturability, ethical, health, safety, social, and political factors depending on the nature of the design.)
4) The ability to develop, select, and use modern techniques and tools required for the analysis and solution of complex problems encountered in mechatronics engineering, robotics, autonomous systems, and automation applications; and the ability to effectively utilize information technologies.
5) The ability to design and conduct experiments, collect data, analyze and interpret results for the investigation of complex problems in mechatronics engineering, robotics, autonomous systems, and automation.
6) The ability to work effectively both individually and in disciplinary and multidisciplinary teams (particularly with mechanical, electrical-electronics, and computer engineering).
7) The ability to communicate effectively in both Turkish and English, both orally and in writing; including effective report writing and comprehension of written reports, preparation of design and production reports, delivering effective presentations, and the ability to give and receive clear and understandable instructions.
8) Awareness of the necessity of lifelong learning required by mechatronics engineering; the ability to access, interpret, and develop knowledge, to follow advancements in science and technology, and to continuously update oneself.
9) The ability to act in accordance with ethical principles; awareness of professional and ethical responsibilities, and knowledge of standards used in mechatronics engineering practices.
10) Knowledge of project management and mechatronics engineering practices such as risk management and change management; awareness of entrepreneurship, innovation, and sustainable development.
11) Knowledge of the impacts of mechatronics engineering applications on health, environment, and safety at universal and societal levels; awareness of contemporary issues and the legal implications of engineering solutions.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	A solid foundation in mathematics, natural sciences, and mechatronics engineering; the ability to apply both theoretical and practical knowledge in these fields to model and solve complex engineering problems.	2
2)	The ability to identify, define, formulate, and solve complex mechatronics engineering problems; and to select and apply appropriate analysis and modeling methods for this purpose.	1
3)	The ability to design complex mechatronics engineering systems, processes, devices, or products to meet specified requirements under realistic constraints and conditions; and to apply modern design methodologies for this purpose. (Realistic constraints and conditions may include economic, environmental, sustainability, manufacturability, ethical, health, safety, social, and political factors depending on the nature of the design.)	1
4)	The ability to develop, select, and use modern techniques and tools required for the analysis and solution of complex problems encountered in mechatronics engineering, robotics, autonomous systems, and automation applications; and the ability to effectively utilize information technologies.
5)	The ability to design and conduct experiments, collect data, analyze and interpret results for the investigation of complex problems in mechatronics engineering, robotics, autonomous systems, and automation.	1
6)	The ability to work effectively both individually and in disciplinary and multidisciplinary teams (particularly with mechanical, electrical-electronics, and computer engineering).	1
7)	The ability to communicate effectively in both Turkish and English, both orally and in writing; including effective report writing and comprehension of written reports, preparation of design and production reports, delivering effective presentations, and the ability to give and receive clear and understandable instructions.	1
8)	Awareness of the necessity of lifelong learning required by mechatronics engineering; the ability to access, interpret, and develop knowledge, to follow advancements in science and technology, and to continuously update oneself.
9)	The ability to act in accordance with ethical principles; awareness of professional and ethical responsibilities, and knowledge of standards used in mechatronics engineering practices.
10)	Knowledge of project management and mechatronics engineering practices such as risk management and change management; awareness of entrepreneurship, innovation, and sustainable development.
11)	Knowledge of the impacts of mechatronics engineering applications on health, environment, and safety at universal and societal levels; awareness of contemporary issues and the legal implications of engineering solutions.

Learning Activity and Teaching Methods

Field Study
Expression
Individual study and homework
Lesson
Reading
Homework
Problem Solving

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Homework

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Laboratory	10	% 20
Homework Assignments	6	% 1
Midterms	1	% 34
Final	1	% 45
total		% 100
PERCENTAGE OF SEMESTER WORK		% 55
PERCENTAGE OF FINAL WORK		% 45
total		% 100

Workload and ECTS Credit Grading

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	2	28
Laboratory	10	2	20
Study Hours Out of Class	14	2	28
Homework Assignments	8	5	40
Midterms	1	10	10
Final	1	10	10
Total Workload			136