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

General course introduction information

Course Code: ENG351
Course Name: Digital Filters and Systems
Course Semester: Fall
Course Credits:
Theoretical Practical Credit ECTS
3 0 3 5
Language of instruction: EN
Course Requisites:
Does the Course Require Work Experience?: No
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 SİNA ALP
Course Lecturer(s): Dr.Öğr.Üyesi SİNA ALP
Course Assistants:

Course Objective and Content

Course Objectives: This course covers the concepts and techniques of modern digital signal processing which are fundamental to all the signal/speech/image processing, applications. The course starts with a detailed overview of discrete-time signals and systems, representation of the systems by means of differential equations, and their analysis using Fourier and z-transforms.
Course Content: This course covers the concepts and techniques of modern digital signal processing which are fundamental to all the signal/speech/image processing, applications. The course starts with a detailed overview of discrete-time signals and systems, representation of the systems by means of differential equations, and their analysis using Fourier and z-transforms.

Learning Outcomes

The students who have succeeded in this course;
Learning Outcomes
1 - Knowledge
Theoretical - Conceptual
1) Design of FIR and IIR filters
2 - Skills
Cognitive - Practical
1) Discretize a continuous systems and represent in observable and controllable form
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
2) Discrete-Time Signals and Systems
3) Z-dönüşümü ve ters z-dönüşümü
4) Analysis of Discrete-Time Systems
5) Frekans domeni analizi (DFT ve FFT)
6) FIR Filter Design
7) Midterm
8) IIR Filter Design
9) Magnitude and Phase Response of Filters
10) Optimization in Filter Design
11) Noise Filtering and Applications
12) Real Time Signal Processing
13) General Review and Final Exam Preparation

Sources

Course Notes / Textbooks: None
References: None

Course-Program Learning Outcome Relationship

Learning Outcomes

1

2

Program Outcomes
1) Adequate knowledge in mathematics, natural sciences, and industrial engineering; ability to apply theoretical and applied knowledge in these areas to model and solve engineering problems.
2) Ability to identify, define, formulate, and solve complex industrial engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose.
3) Ability to design a complex industrial engineering system, process, device, or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include economic, environmental, sustainability, manufacturability, ethical, health, safety, social, and political issues, depending on the nature of the design.)
4) Ability to develop, select, and use modern techniques and tools required for industrial engineering, production problems, and ergonomics applications; ability to effectively use information technologies.
5) Ability to design experiments, conduct experiments, collect data, analyze, and interpret results for the investigation of industrial engineering, production planning, and ergonomics problems.
6) Ability to work effectively both individually and in intra-disciplinary and multidisciplinary teams (particularly in collaboration with computer and mechanical engineering).
7) Ability to communicate effectively in written and oral form in both Turkish and English.
8) Recognition of the necessity of lifelong learning required by industrial engineering; ability to access, interpret, and improve information; ability to follow scientific and technological developments and continuously renew oneself.
9) Awareness of professional and ethical responsibility; competence to contribute to the advancement of the profession.
10) Knowledge of industrial engineering practices in project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11) Knowledge of the universal and societal impacts of industrial engineering practices on health, environment, and safety, as well as contemporary issues; 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) Adequate knowledge in mathematics, natural sciences, and industrial engineering; ability to apply theoretical and applied knowledge in these areas to model and solve engineering problems.
2) Ability to identify, define, formulate, and solve complex industrial engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose.
3) Ability to design a complex industrial engineering system, process, device, or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include economic, environmental, sustainability, manufacturability, ethical, health, safety, social, and political issues, depending on the nature of the design.)
4) Ability to develop, select, and use modern techniques and tools required for industrial engineering, production problems, and ergonomics applications; ability to effectively use information technologies. 1
5) Ability to design experiments, conduct experiments, collect data, analyze, and interpret results for the investigation of industrial engineering, production planning, and ergonomics problems. 2
6) Ability to work effectively both individually and in intra-disciplinary and multidisciplinary teams (particularly in collaboration with computer and mechanical engineering).
7) Ability to communicate effectively in written and oral form in both Turkish and English.
8) Recognition of the necessity of lifelong learning required by industrial engineering; ability to access, interpret, and improve information; ability to follow scientific and technological developments and continuously renew oneself.
9) Awareness of professional and ethical responsibility; competence to contribute to the advancement of the profession. 1
10) Knowledge of industrial engineering practices in project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development. 1
11) Knowledge of the universal and societal impacts of industrial engineering practices on health, environment, and safety, as well as contemporary issues; awareness of the legal consequences of engineering solutions

Learning Activity and Teaching Methods

Lesson
Homework
Project preparation

Assessment & Grading Methods and Criteria

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

Assessment & Grading

Semester Requirements Number of Activities Level of Contribution
Attendance 42 % 0
Project 1 % 30
Midterms 1 % 30
Final 1 % 40
total % 100
PERCENTAGE OF SEMESTER WORK % 60
PERCENTAGE OF FINAL WORK % 40
total % 100

Workload and ECTS Credit Grading

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Project 1 24 24
Homework Assignments 2 16 32
Midterms 1 16 16
Final 1 24 24
Total Workload 138