Predictability of Complex Dynamical Systems / Springer Series in Synergetics Bd.69 (PDF)
(Sprache: Englisch)
This is a book book for researchers and practitioners interested in modeling, prediction and forecasting of natural systems based on nonlinear dynamics. It is a practical guide to data analysis and to the development of algorithms, especially for complex...
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Produktinformationen zu „Predictability of Complex Dynamical Systems / Springer Series in Synergetics Bd.69 (PDF)“
This is a book book for researchers and practitioners interested in modeling, prediction and forecasting of natural systems based on nonlinear dynamics. It is a practical guide to data analysis and to the development of algorithms, especially for complex systems. Topics such as the characterization of nonlinear correlations in data as dynamical systems, reconstruction of dynamical models from data, nonlinear noise reduction and the limits of predicatability are discussed. The chapters are written by leading experts and consider practical problems such as signal and time series analysis, biomedical data analysis, financial analysis, stochastic modeling, human evolution, and political modeling. The book includes new methods for nonlinear filtering of complex signals, new algorithms for signal classification, and the concept of the "Global Brain".
Bibliographische Angaben
- 2012, 1996, 234 Seiten, Englisch
- Herausgegeben: Yurii A. Kravtsov, James B. Kadtke
- Verlag: Springer Berlin Heidelberg
- ISBN-10: 3642802540
- ISBN-13: 9783642802546
- Erscheinungsdatum: 06.12.2012
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: PDF
- Größe: 23 MB
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- Vorlesefunktion
Sprache:
Englisch
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