Application of wavelets in numerical simulations

Application of wavelets in numerical simulations

1.

Subject title

Application of wavelets in numerical simulations

Примена на бранчиња во нумерички симулации

2.

Code

m23_w_007

3.

Study program

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

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 / Зимски

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Весна Димитриевска Ристовска

9.

Prerequisites for enrollment

10.

Subject goals and competencies:


The student to gain basic knowledge of numerical methods and transformations with waves (Weedletti) to be able to apply them in mathematical modeling of troubles. Applying Weedletti to numerically resolving equations, mathematical modeling of bioinformatics problems, image compression and noise removal. Using ready -made software packages to illustrate the application of Welder.

11.

Subject content:


Introduction: Application of Waves (Weeds) in Mathematical Modeling. Basic types of errors and sources of error. Polynomial, SPINA and Wailett interpolation. Approximation of Functions: Tangent Method, Newton`s Method, Nonlinear Welett Method. Numerical integration and numerical resolution differential equations. Welet methods in solving partial differential and integral equations, solving bioinformatics problems, image compression and noise removal. Using ready -made software packages to illustrate the application of Welder.

12.

Learning methods:


Предавања поддржани со презентации преку слајдови, интерактивни предавања, вежби (користење на опрема и софтверски пакети), тимска работа, пример случаи, поканети гости предавачи, самостојна изработка и одбрана на проектна задача и семинарска работа, учење во електронско опкружување (форуми, консултации).

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

60 + 0 + 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

0 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

15 points

17.2.

Seminar work / project (presentation: written and oral)

45 points

17.3.

Activities and learning

15 points

17.4.

Final exam

0 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

20.

Language of instruction

македонски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

No.

Author

Title

Publisher

Year

6721

K. Urban

Wavelets in Numerical Simulations

Springer

2002

6722

H.G. Stark

Wavelets and Signal Processing

Springer-Verlag Berlin Heidelberg

2005

6723

D.P. Radunovi´c

Talasi´ci

Akademska misao, Beograd

2005

22.2.

Additional literature

No.

Author

Title

Publisher

Year