Mathematics – Dynamical Systems
Scientific paper
Feb 1990
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1990phrva..41.1782a&link_type=abstract
Physical Review A - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, 3rd Series (ISSN 0556-2791), vol
Mathematics
Dynamical Systems
44
Chaos, Fourier Analysis, Nonlinear Systems, Prediction Analysis Techniques, Time Series Analysis, Dynamical Systems, Liapunov Functions, Power Spectra, System Identification
Scientific paper
The present treatment of prediction and system identification in time-series having broadband power spectra generated by the intrinsic nonlinear dynamics of the system views that system in a reconstructed space that captures the (often strange) attractor on which the system evolves. A procedure is given for the construction of parameterized maps which evolve points in the phase-space into the future; since the predictor of future points is a combination of operation on past points by the map and its iterates, the map is viewed as a dynamical system, and not merely as a fit to the data. Attention is given to methods for the extraction of the Liapunov exponents and optimum moments from data, as well as to problems associated with prediction and systems identification on strange attractors.
Abarbanel Henry D. I.
Brown Reggie
Kadtke James B.
No associations
LandOfFree
Prediction in chaotic nonlinear systems - Methods for time series with broadband Fourier spectra does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Prediction in chaotic nonlinear systems - Methods for time series with broadband Fourier spectra, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Prediction in chaotic nonlinear systems - Methods for time series with broadband Fourier spectra will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1843465