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 DİDEM KIVANÇ TÜRELİ

Course Lecturer(s):

Dr.Öğr.Üyesi DİDEM KIVANÇ TÜRELİ

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) Sufficient knowledge in mathematics, science and engineering related to their branches; and the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
2) The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
3) The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4) Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5) Ability to design experiments, conduct experiments, collect data, analyze and interpret results to examine engineering problems or discipline-specific research topics.
6) The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7) Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge; ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8) Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9) Conform to ethical principles, and standards of professional and ethical responsibility; be informed about the standards used in engineering applications.
10) Awareness of applications in business, such as project management, risk management and change management; awareness of entrepreneurship, and innovation; information about sustainable development.
11) Information about the universal and social health, environmental and safety effects of engineering applications and the ways in which contemporary problems are reflected in the engineering field; awareness of the legal consequences 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)	Sufficient knowledge in mathematics, science and engineering related to their branches; and the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.	2
2)	The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.	1
3)	The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)	1
4)	Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5)	Ability to design experiments, conduct experiments, collect data, analyze and interpret results to examine engineering problems or discipline-specific research topics.	1
6)	The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.	1
7)	Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge; ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.	1
8)	Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9)	Conform to ethical principles, and standards of professional and ethical responsibility; be informed about the standards used in engineering applications.
10)	Awareness of applications in business, such as project management, risk management and change management; awareness of entrepreneurship, and innovation; information about sustainable development.
11)	Information about the universal and social health, environmental and safety effects of engineering applications and the ways in which contemporary problems are reflected in the engineering field; awareness of the legal consequences 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