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19D081NA - Numerical Analysis

Course specification
Course title Numerical Analysis
Acronym 19D081NA
Study programme Electrical Engineering and Computing
Module Applied Mathematics
Type of study doctoral studies
Lecturer (for classes)
Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
      ESPB 9.0 Status elective
      Condition Knowledge of classical mathematical analysis, notion of basic terms and methods of numerical analysis.
      The goal Introducing students to methods of function approximation, numerical methods for solving equations and systems of equations, ways of choosing appropriate methods depending on nature of problems, guiding students to independently conduct research and follow contemporary topics in this field.
      The outcome Students are capable to apply methods of numerical analysis in electrotechnics and to conduct independent research and follow contemporary topics in this field.
      Contents
      Contents of lectures Orthogonal systems of functions. Approximations of functions. Hermite's interpolation polynomial, spline interpolation. Iterative processes and convergence. Aitken delta 2 process. Numerical solving of systems of nonlinear equations, differential, integral and complex equations. Some methods of numerical integration. Iterative methods on spaces with nondeterministic distances.
      Contents of exercises Application of mathematical software tools for implementation of numerical methods for solving problems in electrotechnics and computer science.
      Literature
      1. D. Đ. Tošić, Uvod u numeričku analizu, Akademska misao, Beograd 2004. (Original title)
      2. D. Radunović, Numeričke metode, Akademska misao, Beograd 2000. (Original title)
      3. D. Herceg, N. Krejić, Numerička analiza, STILOS,1997. (Original title)
      Number of hours per week during the semester/trimester/year
      Lectures Exercises OTC Study and Research Other classes
      8
      Methods of teaching Classic lectures, with the use of computers and modern mathematical software packages. Also, mentoring work with candidates, consultations.
      Knowledge score (maximum points 100)
      Pre obligations Points Final exam Points
      Activites during lectures Test paper 30
      Practical lessons 50 Oral examination 20
      Projects
      Colloquia
      Seminars