MS20 ~ Monday, May 22, 1995 ~ 10:00 AM
Modeling Nonlinear Dynamical Systems:
For several years there has been an enormous effort devoted to modeling nonlinear dynamical systems from time series data. These methods typically begin with a time series and, after phase space reconstruction, produce a model capable of predicting the time evolution of initial conditions in the phase space. What has been absent is a discussion of the question: What good are these models? The speakers of this minisymposia will address this question. After presenting a modeling procedure each speaker will discuss how the model can be used address a problem of practical, industrial, or commercial interest.
Organizer: Reggie Brown, University of California, San Diego
- Chaos and Detection
- Andrew M. Fraser, Portland State University; and Qin Cai, University of Texas, Austin
- Predicting Noisy Time Series
- Andreas Weigend, University of Colorado, Boulder
- Nonlinear Modeling - Why Bother?
- Stephen Eubank, Los Alamos National Laboratory
- Using Models to Diagnose, Test, and Control Chaotic Systems
- Reggie Brown, Organizer