Basics of Convex Optimization with Application

Објавено: October 12, 2018
  1.    Course Title Basics of Convex Optimization with Application
  2.    Code 3ФЕИТ08З013
  3.    Study program TKII
  4.    Organizer of the study program (unit, institute, department) Faculty of Electrical Engineering and Information Technologies
  5.    Degree (first, second, third cycle) First cycle
  6.    Academic year/semester IV/7   7.    Number of ECTS credits 6.00
  8.    Lecturer Dr Katerina Hadji-Velkova Saneva, Dr Zoran Hadji-Velkov
  9.    Course Prerequisites

10.    Course Goals (acquired competencies):  Familiarization with the basic theory of convex optimization. Recognizing and solving convex optimization problems for electrical engineering.

11.    Course Syllabus: The notion of mathematical optimization. Importance of convex optimization in electrical engineering and ICT (examples). Convexity versus nonconvexity. Optimization without restriction. Illustrative examples of electrical engineering. Convex sets. Convex functions. Convex optimization problems. Equivalent problems. Criteria for optimum. Duality. Lagrange Function. Conditions for optimum. The Karush-Kuhn-Tucker theorem. Convex optimization with least squares. Linear programming. Application in optimization of signal strength. Application of numerical algorithms in optimization problems. Internal point method. Using CVX solver in Matlab. Convex relaxation. Application in optimum design of systems and networks. Optimization problems in telecommunication engineering. Application in optimization of ICT-based systems.
12.    Learning methods:  Lectures, Classroom exercises, Seminar works / projects, independent work
13.    Total number of course hours 3 + 2 + 0 + 0
14.    Distribution of course hours 180
15.    Forms of teaching 15.1. Lectures-theoretical teaching 45
15.2. Exercises (laboratory, practice classes), seminars, teamwork 30
16.    Other course activities 16.1. Projects, seminar papers 20
16.2. Individual tasks 20
16.3. Homework and self-learning 65
17.    Grading 17.1. Exams 0
17.2. Seminar work/project (presentation: written and oral) 30
17.3. Activity and participation 20
17.4. Final exam 50
18.    Grading criteria (points) 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.    Conditions for acquiring teacher’s signature and for taking final exam Аttend classes regularly
20.    Forms of assessment During the semester, two partial written exams are foreseen (at the middle and at the end of the semester). For students who have passed the partial exams, a final oral exam can be conducted. The final grade includes the points from the partial exams, the points from the individual student work (homeworks), and the final oral exam.
Students who take one written exam instead of two partial exams can take it in the scheduled exam sessions. For the student who has passed the written exam, a final oral exam can be conducted. The final grade includes the points from the written exam, the points from the individual student work (homeworks), and the final oral exam
21.    Language Macedonian and English
22.    Method of monitoring of teaching quality Internal evaluation and surveys
23.    Literature
23.1. Required Literature
No. Author Title Publisher Year
1 S. Boyd and L. Vandenberghe Convex Optimization Cambridge University Press 2004