MAK460 Signal Processing in Mechanical EngineeringInstitutional InformationDegree Programs Mechanical EngineeringInformation For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
Mechanical Engineering

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Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course General Introduction Information

Course Code: MAK460
Course Name: Signal Processing in Mechanical Engineering
Course Semester: Spring
Course Credits:
ECTS
6
Language of instruction:
Course Requirement:
Does the Course Require Work Experience?: No
Type of course: Area Ellective
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 : Ar.Gör. İSMAİL SAĞDIÇ
Course Lecturer(s):
Course Assistants:

Course Purpose and Content

Course Objectives: used in the analysis and representation of digital (discrete) signals and systems are taught.
Course Content: Sampling and reconstruction. Introduction to discrete time signals and systems. Linear time invariant (LTI) systems; convolution sum. Discrete transformations; DFT, FFT, DCT, DST. Z-transform and its applications. Analysis of LTI systems in the transformation plane. Design of filters with finite impulse response. Design of filters with infinite impulse response. Digital Signal Processors. Digital signal processing applications.

Learning Outcomes

The students who have succeeded in this course;
1) Can describe and analyze discrete time signals and systems in time and frequency domain.
2) Applies digital signal processing methods to analyze discrete-time signals and systems.
3) Applies digital signal processing methods to design discrete-time systems.
4) Designs and implements digital filters.
5) Solve digital signal processing problems using Matlab.

Course Flow Plan

Week Subject Related Preparation
1) Sampling and reconstruction. Course Notes
2) Discrete time signals and systems: classification and properties. Course Notes
3) Linear time-invariant systems: convolution summation. Course Notes
4) LTI-causal systems defined by linear difference equations with constant coefficients. Course Notes
5) Discrete transformations: DFT, FFT, DCT and DST. Course Notes
6) Discrete transformations: DFT, FFT, DCT and DST (continued). I. Homework. Course Notes
7) Z-transform and its applications. Course Notes
8) Midterm Exam
9) Z-transform and its applications (continued). Course Notes
10) Analysis of LTI systems in the transformation plane. Course Notes
11) Analysis of LTI systems in the transformation plane (continued). Course Notes
12) Design of digital filters with finite impulse response. Course Notes
13) Design of digital filters with infinite impulse response Course Notes
14) Digital Signal Processors. Course Notes
15) Digital signal processing applications. Course Notes
16) Final Exams
17) Final Exams

Sources

Course Notes / Textbooks: Ders Notları
References: Discrete-Time Signal Processing, 3/E. 2010. Alan V. Oppenheim and. Ronald W. Schafer. Pearson Prentice Hall Digital Signal Processing. A Computer-Based Approach. 1998. Sanjit K. Mitra.McGraw-Hill

Course - Learning Outcome Relationship

No Effect 1 Lowest 2 Medium 3 Highest
       
Program Outcomes Level of Contribution
1) Ability to utilize advanced theoretical and applied knowledge in the field. 3
2) Using the advanced knowledge and skills acquired in the field, being able to interpret and evaluate data, identify problems, analyze them, and develop solution proposals based on research and evidence. 3
3) Being able to organize and implement projects and activities for the social environment in which one lives with a sense of social responsibility.
4) Being able to follow information in one foreign language at least at the European Language Portfolio B1 General Level and communicate with colleagues in the field.
5) Ability to use information and communication technologies together with at least European Computer Driving License Advanced Level computer software, as required by the field. 3
6) Being able to evaluate advanced knowledge and skills in the field critically. 3
7) Identifying learning needs and being able to direct learning. 3
8) Developing a positive attitude towards lifelong learning.
9) Acting in accordance with social, scientific, cultural, and ethical values ​​in the stages of collecting, interpreting, applying, and announcing the results related to the field.
10) Having sufficient awareness about the universality of social rights, social justice, quality culture, preservation of cultural values, as well as environmental protection, occupational health, and safety.
11) Being able to conduct an advanced study independently in the field.
12) To take responsibility individually and as a team member to solve complex problems encountered in the field of application, which are unforeseen.
13) Being able to plan and manage activities for the development of those under their responsibility within the framework of a project.
14) Possess advanced level theoretical and practical knowledge supported by textbooks with updated information, practice equipments and other resources. 3
15) Being able to inform relevant individuals and institutions about the field; expressing their thoughts and solution proposals for problems both in written and verbal form. 3
16) Being able to share your thoughts and solutions regarding subjects related to the field with both experts and non-experts, supported by quantitative and qualitative data. 3

Learning Activity and Teaching Methods

Bireysel çalışma ve ödevi
Course
Proje Hazırlama

Measurement and Evaluation Methods and Criteria

Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama)
Homework

Assessment & Grading

Semester Requirements Number of Activities Level of Contribution
Homework Assignments 1 % 20
Project 1 % 20
Midterms 1 % 20
Final 1 % 40
total % 100
PERCENTAGE OF SEMESTER WORK % 60
PERCENTAGE OF FINAL WORK % 40
total % 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities Number of Activities Aktiviteye Hazırlık Aktivitede Harçanan Süre Aktivite Gereksinimi İçin Süre Workload
Course Hours 14 3 42
Study Hours Out of Class 14 7 98
Homework Assignments 1 25 25
Midterms 1 2 2
Final 1 2 2
Total Workload 169