Navigation

26E083OPM3 - Selected Topics in Mathematics 3 with Applications

Course specification
Course title Selected Topics in Mathematics 3 with Applications
Acronym 26E083OPM3
Study programme Electrical Engineering and Computing
Module Computer Engineering and Informatics
Type of study bachelor academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB 3.0 Status elective
Condition
The goal Familiarizing students with the concepts of mathematical analysis in n-dimensional real space and methods to determine extreme values of multivariable real functions, convex sets and multivariable convex functions, with the goal to be able to solve problems of applied mathematics in various areas of Electrical and Computer Engineering.
The outcome The student is competent to determine extreme values of multivariable real functions and multivariable convex functions and to apply these techniques to solve problems in various fields of Electrical and Computer Engineering.
Contents
Contents of lectures Multivariable functions: differentiability, differential operators, extreme values, Taylor’s formula, unconditional and conditional extreme values, Lagrange multipliers, Karush-Kuhn-Tucker theorem, convex sets, multivatiable convex functions, first and second order convexity conditions.
Contents of exercises Through examples and problems, students learn how to apply the theorems and concepts learned in theory, and to solve specific problems using mathematical software such as Matlab and Python with libraries. Students are prepared to solve optimisation problems in Electrical and Computer Engineering.
Literature
  1. Siniša Ješić: Script in Mathematics 3, Multivariable functions, Theory of integrals, Belgrade 2007, in serbian
  2. Siniša Vrećica, Convex analysis, second edition, Universitz of Belgrade, Faculty of Mathematics, 1999, in serbian
  3. Boyd, S.,Vandenberghe, L. Convex optimization. Cambridge university press, 2004 (Original title)
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
1 1 0.5
Methods of teaching Lectures, exercises, discussions, help with homework using mathematical software such as Matlab and Python with libraries
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures 0 Test paper 50
Practical lessons 30 Oral examination 20
Projects
Colloquia 0
Seminars 0