MENÜ MENÜ  

cover

Computation of invariant measures with dimension reduction methods

Jens Kemper

ISBN 978-3-8325-2452-4
158 Seiten, Erscheinungsjahr: 2010
Preis: 37.00 €
Computation of invariant measures with dimension reduction methods
In recent years, Dellnitz, Junge and co-workers developed a subdivision algorithm for the approximation of invariant measures in discrete dynamical systems based on the so-called Ulam's approach. In high dimensions, this adaptive invariant measure (AIM) algorithm suffers from the ``curse of dimension'' even when the support of the system's invariant measure is known to be low-dimensional.

In our thesis we develop algorithms facing this problem by combining the subdivision technique with proper orthogonal decomposition (POD) as a model reduction method. We derive explicit error bounds concerning the long-time behavior of POD solutions, propose a discrete version of the Prohorov metric as a proper distance notion for discrete measures computed by the algorithms, and analytically compare the approximation processes of the AIM algorithm and the POD-based algorithms.

A marginal-like representation of discrete measures is proposed in order to visualize the numerical experiments. The algorithms are applied to finite element discretizations of the Chafee-Infante problem in order to show the power of our approach.

Keywords:
  • Numerische Methoden
  • Invariante Maße
  • Dimensionsreduktion
  • Partielle Differentialgleichungen
  • Mengenwertige Algorithmen

KAUFOPTIONEN

37.00 €
auf Lager
Versandkostenfrei innerhalb Deutschlands


Wollen auch Sie Ihre Dissertation veröffentlichen?

cover cover cover cover cover cover cover cover cover