|
Instructors: Chen Li; Univ.-Prof. Dr. Michael Wand
Event type:
Lecture/practice class
Displayed in timetable as:
Modellierung I
Hours per week:
4
Credits:
6,0
Language of instruction:
German
Min. | Max. participants:
- | -
Requirements / organisational issues:
Essential:
- Basic Mathematics: Core lectures from Bachelor Computer Science (Calculus, Algebra, Basic Statistics) or equivalent knowledge (for example, from a related diszipline).
- Good programming skills („Einführung in die Programmierung“, „Einführung in die Softwareentwicklung“, „Datenstrukturen und Algorithmen“ or equivalent).
Useful:
- C++ knowledge: Tutorials will use C++ (other languages are permitted but this might require some additional effort).
- Basics of computer graphics are useful, but not required (plan for a bit of extra time, in case).
Contents:
Overview of Modeling I
The lecture discusses basic concepts of how to model real-world phenomena with a computer. The goal is to give an overview of basic mathematical and theoretical tools for modeling, and (in particular) to bring these concepts into practical implementation and application.
Modeling of real-world phenomena poses a number of questions:
- Representation: Which information is constitutes the state of the modeled phenomenon?
- Rules/dynamics: How does the phenomenon evolve/behave over time / space?
- Simulation: How can we simulate it?
- Inverse problems: Can we adjust the model parameter such that the simulation explains real-world measurement data?
Bottom Line: Modelling I = Linear Modelling
Modelling 1 is the first part of a two-lecture series. It will focus on linear models (state as vector in a linear space). It will discuss representations and sampling issues, and show a number of practical examples (such as global illumination or dynamicals of objects). For inverse problems, we consider simple quadratic variational formulations that can be solved with the nice & easy to use linear algebra tools.
The second part (Modelling 2) will go deeper into the area of non-linear models (non-linear optimization, differential geometry). It is regularly held in the corresponding upcomming winter semester.
Additional information:
This is a series of two lectures. Both are suitable for both advanced (last year) Bacholor students or Masterstudents in computer science or students from other disciplines with a suitable background (mathematics & programming skills).
|
