Course Advanced Mathematics


Responsible: Prof.Dr. Schellong

Course

Meets requirements of following modules(MID)

Course Organization

Version
created 2013-04-29
VID 2
valid from WS 2012/13
valid to
Course identifiers
Long name Advanced Mathematics
CID F07_HIM
CEID (exam identifier)

Contact hours per week (SWS)
Lecture 2
Exercise (unsplit) 2
Exercise (split)
Lab
Project
Seminar
Tutorial(voluntary) 2
Total contact hours
Lecture 30
Exercise (unsplit) 30
Exercise (split)
Lab
Project
Seminar
Tutorial (voluntary) 30
Max. capacity
Exercise (unsplit)
Exercise (split) 40
Lab 18
Project 18
Seminar 40

Total effort (hours): 150

Instruction language

  • English

Study Level

  • Graduate

Prerequisites

  • Real functions of one or more variables
  • Differential and integral calculus
  • Linear algebra (linear equation systems, matrix calculus)
  • Basic skills in procedural programming

Textbooks, Recommended Reading

  • Papula: Mathematik für Ingenieure und Naturwissenschaftler, Band 3 (Vieweg)
  • Koop, Moock: Lineare Optimierung (Spektrumverlag)
  • Zimmermann: Operations Research (Vieweg)

Instructors

  • Prof.Dr. Schellong

Supporting Scientific Staff

Transcipt Entry

Advanced Mathematics

Assessment

Type
we written exam

Total effort [hours]
we written exam

Frequency: 3/year


Course components

Lecture/Exercise

Objectives

Contents
  • mathematical models of theoretical electrical engineering
    • scalar and vector fields
    • differential operators
    • line integral
    • surface integral
    • integral theorems
    • mathematical models for electrical dynamics
  • Technische Systeme optimieren
    • mathematical optimization models
      • general optimization model
      • classification
      • optimization procedures
    • linear optimization model
      • description
      • graphical solution
      • normal form
      • basis solution
    • simplex procedure
      • simplex tableau
      • basis change
      • primal simplex procedure
    • theory of duality
      • dual simplex tableau
      • dual simplex procedure
    • transport problems
      • description
      • optimal solution
    • simulation tools

Acquired Skills
  • mathematical models
    • mathematical description of applied problems
      • optimization
      • physics
    • application of mathematical models
      • electrical dynamics
      • optimal scheduling of power plants
  • optimization procedures
    • selection of appropriate algoritms
    • construction of algorithms
    • implementation of algorithms
    • numerical simulation
    • evaluation of the results

Additional Component Assessment

Type
fPS exercise (on course and self study)

Contribution to course grade
fPS unrated

Frequency:

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