Advanced coding algorithms

1.

Subject title

Advanced coding algorithms

Напредни алгоритми за кодирање

2.

Code

m23_s_028

3.

Study program

Cloud Computing, IT management, Bioinformatics, Eco-informatics, Inteligent Systems, Internet Technologies and cyber security, Computer Science, Statistics and Data Analytics, Software for embedded systems, Software Engineering, Cloud Computing, Bioinformatics, Security, Cryptography and Coding, Statistics and Data Analytics, Data science in computer science and engineering, Еducation with ICT, IT management, Software Engineering, Security, Cryptography and Coding,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Втор циклус

6.

Academic year / semester

5 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Александра Поповска Митровиќ проф. д-р Наташа Илиевска проф. д-р Верица Бакева

9.

Prerequisites for enrollment

10.

Subject goals and competencies:

The purpose of the course is to deepen the knowledge of the coding theory and study of advanced and new aspects in the code fixing and detection code. Iterative and algebraic decoding methods will be considered. The course provides for the elaboration of papers with new results of coding theory.

11.

Subject content:

Iterative decoding methods: Turbo codes Decoding with probabilities (Posteriori Probability (App) Decoding) Statistical Analysis Methods (Monte-Caro Simulations and Exit-Chart Analysis) LDPC Codes (Low Density Single Parity Check) Representing LDPC codes with matrix and graphs Construction of the code Iterative decoding with Message Passing Statistical and Graph-based Analysis Methods (Density Evolution, Stopping Sets) Algebraic decoding methods: Syndrome decoding Reed-solomone codes Decoding with Peterson-Gorenstein-Zierler and Forne algortes IRS codes (Interleaved Reed-Solomon) Interpolation -based techniques Interpretation of the decoding problem as a problem of polynomial interpolation Sudan`s algorithm Decoding with a list Quasi -group -based detection and repair codes.

12.

Learning methods:

Предавања, проекти, дискусии, работилници

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

60 + + 45 + 45 + 30 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

60 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

hours

16.

Other forms of activities

16.1.

Project tasks

45 hours

16.2.

Independent tasks

45 hours

16.3.

Homework

30 hours

17.

Grading method

17.1.

Tests

0 points

17.2.

Seminar work / project (presentation: written and oral)

45 points

17.3.

Activities and learning

0 points

17.4.

Final exam

50 points

18.

Grading criteria (points / grade)

up to 50 points

5 (five) (F)

from 51 to 60 points

6 (six) (E)

from 61 to 70 points

7 (seven) (D)

from 71 to 80 points

8 (eight) (C)

from 81 to 90 points

9 (nine) (B)

from 91 to 100 points

10 (ten) (A)

19.

Condition for signature and taking final exam

Реализирани активности 15, 16

20.

Language of instruction

Македонски и алглиски

21.

Quality assurance method

Механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

22.2.

Additional literature