MEC460 Makine Mühendisliğinde İşaret İşlemeInstitutional InformationDegree Programs Mechanical Engineering (English)Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
Mechanical Engineering (English)

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

Course General Introduction Information

Course Code: MEC460
Course Name: Makine Mühendisliğinde İşaret İşleme
Course Semester: Fall
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) Having advanced theoretical and practical knowledge supported by textbooks, application tools and other resources containing current information in the field. 3
2) Ability to use advanced theoretical and practical knowledge acquired in the field. 3
3) Ability to interpret and evaluate data, identify and analyze problems, and develop solution suggestions based on research and evidence, using the advanced knowledge and skills acquired in the field. 3
4) To be able to inform relevant people and institutions on issues related to the field; Ability to convey thoughts and solution suggestions to problems in written and oral form. 3
5) Ability to share one's thoughts on issues related to one's field and solutions to problems, supported by quantitative and qualitative data, with experts and non-experts. 3
6) Ability to organize and implement projects and events for the social environment in which one lives with awareness of social responsibility.
7) Ability to monitor knowledge in the field and communicate with colleagues by using a foreign language at least at the European Language Portfolio B1 General Level.
8) Ability to use information and communication technologies along with computer software at least at the Advanced Level of the European Computer Usage License required by the field.
9) Acting in accordance with social, scientific, cultural and ethical values during the collection, interpretation, application and announcement of the results of data related to the field.
10) Having sufficient awareness about the universality of social rights, social justice, quality culture and protection of cultural values, environmental protection, occupational health and safety.
11) Ability to evaluate the advanced knowledge and skills acquired in the field with a critical approach. 3
12) Ability to identify learning needs and direct learning
13) Being able to develop a positive attitude towards lifelong learning.
14) Ability to independently carry out an advanced study related to the field.
15) Ability to take responsibility individually and as a team member to solve unforeseen complex problems encountered in field-related applications.
16) Ability to plan and manage activities aimed at the development of the employees under his/her responsibility within the framework of a project.

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