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

Ders Genel Tanıtım Bilgileri

Course Code:

1410002035

Ders İsmi:

Introduction to Coding Theory

Ders Yarıyılı:

Fall

Ders Kredileri:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Bölüm Seçmeli

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 :

Assoc. Prof. Esengül SALTÜRK

Course Lecturer(s):

Assoc. Prof. Esengül SALTÜRK

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	The goal of the course is to introduce Coding Theory as one of the important applications of algebra and so give the connections between mathematics and engineering applications of error correcting codes.
Course Content:	Communication channel. Problems in coding theory. Error detection and correction. Hammming distance. Singleton bound and MDS codes. Hamming bound and perfect codes. Encoding and decoding with a linear code. Constructing new codes from exiting ones.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Mathematical background behind the theory of error correcting codes.
2) Theoretical background in the field of digital data (information) transferring.
2 - Skills
Cognitive - Practical
1) Understanding the concept of decoding and application of decoding techniques.
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	Communication channel. Symmetric channel. Block codes. Hamming distance. Nearest Neighbour Decoding rule.
2)	Error detection and correction. Minimum Hamming distance. Parameters of a code. Fundamental problems in coding theory.
3)	Erasures. Singleton bound and MDS codes. Hamming bound and perfect codes.
4)	Maximum Likelihood Decoding rule and probability.
5)	Vektör uzayları. Doğrusal (lineer) kodlar. Hamming ağırlık.
6)	Equivalence. Generator matrix. Encoding with a linear code.
7)	The dual of a linear code. Parity-check matrix.
8)	Midterm
9)	Decoding linear codes. Syndrome table and syndrome decoding.
10)	Constructing new codes from old. Extended code. Punctured code. Shortened code.
11)	Direct sum construction. Plotkim sum construction.
12)	Hamming codes. Decoding Hamming codes.
13)	Extended Hamming code. Decoding for a an extended Hamming code.
14)	Golay codes. Decoding Golay codes.
15)	Nonlinear codes. Hadamard codes. Nordstrom–Robinson codes. Preparata codes. Kerdock Codes

Sources

Course Notes / Textbooks:	Textbook: https://sites.google.com/view/discretemathematicsresources/home A free resource material: Advanced Topics 6. Coding Theory, Cristina Fernandez-Cordoba and Merce Villanueva, 2021. Diğer kaynak kitap: San Ling, Chaoping Xing, Coding Theory-A first course, Cambridge University Press, 2004.
References:	Textbook: https://sites.google.com/view/discretemathematicsresources/home A free resource material: Advanced Topics 6. Coding Theory, Cristina Fernandez-Cordoba and Merce Villanueva, 2021. Other reference book: San Ling, Chaoping Xing, Coding Theory-A first course, Cambridge University Press, 2004.

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	3
Program Outcomes
1) PO 1.1) Sufficient knowledge in mathematics, science and computer engineering
2) PO 1.2) Ability to apply theoretical and applied knowledge in mathematics, science and computer engineering for modeling and solving engineering problems.
3) PO 2.1) Identifying complex engineering problems
4) PO 2.2) Defining complex engineering problems
5) PO 2.3) Formulating complex engineering problems
6) PO 2.4) Ability to solve complex engineering problems
7) PO 2.5) Ability to choose and apply appropriate analysis and modeling methods
8) PO 3.1) Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions.
9) PO 3.2) Ability to apply modern design methods under realistic constraints and conditions for a complex system, process, device or product
10) PO 4.1) Developing modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications
11) PO 4.2) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications
12) PO 4.3) Ability to use information technologies effectively.
13) PO 5.1) Examination of complex engineering problems or discipline-specific research topics, designing experiments
14) PO 5.2) Examination of complex engineering problems or discipline-specific research topics, experimentation
15) PO 5.3 ) Analysis of complex engineering problems or discipline-specific research topics, data collection
16) PO 5.4) Analyzing the results of complex engineering problems or discipline-specific research topics
17) PO 5.5) Examining and interpreting complex engineering problems or discipline-specific research topics

Ders - Öğrenme Kazanımı İlişkisi

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

	Program Outcomes	Level of Contribution
1)	PO 1.1) Sufficient knowledge in mathematics, science and computer engineering	5
2)	PO 1.2) Ability to apply theoretical and applied knowledge in mathematics, science and computer engineering for modeling and solving engineering problems.	4
3)	PO 2.1) Identifying complex engineering problems	4
4)	PO 2.2) Defining complex engineering problems	4
5)	PO 2.3) Formulating complex engineering problems
6)	PO 2.4) Ability to solve complex engineering problems
7)	PO 2.5) Ability to choose and apply appropriate analysis and modeling methods
8)	PO 3.1) Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions.
9)	PO 3.2) Ability to apply modern design methods under realistic constraints and conditions for a complex system, process, device or product
10)	PO 4.1) Developing modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications
11)	PO 4.2) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications
12)	PO 4.3) Ability to use information technologies effectively.
13)	PO 5.1) Examination of complex engineering problems or discipline-specific research topics, designing experiments
14)	PO 5.2) Examination of complex engineering problems or discipline-specific research topics, experimentation
15)	PO 5.3 ) Analysis of complex engineering problems or discipline-specific research topics, data collection
16)	PO 5.4) Analyzing the results of complex engineering problems or discipline-specific research topics
17)	PO 5.5) Examining and interpreting complex engineering problems or discipline-specific research topics	4

Öğrenme Etkinliği ve Öğretme Yöntemleri

Bireysel çalışma ve ödevi
Grup çalışması ve ödevi
Homework
Problem Çözme
Proje Hazırlama

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

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

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	1	% 30
Midterms	1	% 30
Semester Final Exam	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	Duration (Hours)	Workload
Course Hours	14	3	42
Homework Assignments	1	104	104
Midterms	1	3	3
Final	1	3	3
Total Workload			152