Modeling Nonlinear Dynamical Systems: Applications . . . (MS20)

MS20 ~ Monday, May 22, 1995 ~ 10:00 AM

Modeling Nonlinear Dynamical Systems: Applications

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

3/15/95