The seminar will give an introduction to techniques from time series analysis, parameter estimation and automatic dimension reduction applied to the automated generation of models for the effective dynamics of complex systems with many degrees of freedom.
Each morning, two lectures will introduce fundamental concepts and their respective algorithmic realization in the following fields:
- Markov chains and Hidden Markov Models,
- Standard linear vs. non-linear approaches to time series analysis in multiple dimensions,
- Dimension reduction and qualitative dynamics,
- Parameterization of stochastic differential equations,
- Combination of time series analysis, dimension reduction and parameter estimation for complex systems with many degrees of freedom.
- molecular dynamics,
- climate and atmosphere dynamics and
- to the dynamical behaviour of economic systems.
The seminar will be devised for an interdisciplinary audience. Some background in numerical mathematics, stochastics/statistics, and linear algebra will be required and students with some expertise in the two first fields are especially welcome. A detailed manuscript will be made available.
- full name and address, including e-mail address
- present position, university
- name of supervisor of Ph.D. thesis
- a short summary of previous work and interest
should be sent as hard copy or by e-mail (.ps or .pdf file) to:
Prof. Dr. Gert-Martin Greuel
Universität Kaiserslautern
Fachbereich Mathematik
Erwin Schrödingerstr.
67663 Kaiserslautern, Germany
.