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13D081NA - Numerical Analysis

Course specification
Course title Numerical Analysis
Acronym 13D081NA
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.Dj. Tosic, Introduction to Numerical Analysis, Akademska misao, Belgrade 2004.
      2. D. Radunovic, Numerical Methods, Akademska misao, Belgrade 2000.
      3. D. Herceg, N. Krejic, Numerical Analysis, STILOS 1997.
      4. S. Jesic, Theory of functions on fuzzy metric spaces, script, Belgrade 2006.
      Number of hours per week during the semester/trimester/year
      Lectures Exercises OTC Study and Research Other classes
      6
      Methods of teaching Traditional lectures with use of computers and modern mathematical software tools. Mentoring work with students, consultations, e-mail communications.
      Knowledge score (maximum points 100)
      Pre obligations Points Final exam Points
      Activites during lectures 0 Test paper 50
      Practical lessons 0 Oral examination 20
      Projects
      Colloquia 30
      Seminars 0