Predictability of Complex Dynamical Systems, Softcover reprint of the original 1st ed. 1996
Coll. Springer Series in Synergetics, Vol. 69

Coordinators: Kravtsov Yurii A., Kadtke James B.

Language: French

Approximative price 52.74 €

In Print (Delivery period: 15 days).

Add to cartAdd to cart
Publication date:
234 p. · 15.5x23.5 cm · Paperback
Introduction. Time series analysis : the search for determinism. Dynamical modelling and forecasting algorithms. Prediction of biological systems. Analysis and forecasting of financial data. Socio-political and global problems.
1 Introduction.- 2 Time Series Analysis: The Search for Determinism.- Method to Discriminate Against Determinism in Time Series Data.- Observing and Predicting Chaotic Signals: Is 2% Noise Too Much?.- A Discriminant Procedure for the Solution of Inverse Problems for Non-stationary Systems.- Classifying Complex, Deterministic Signals.- 3 Dynamical Modeling and Forecasting Algorithms.- Strategy and Algorithms of Dynamical Forecasting.- Parsimony in Dynamical Modeling.- The Bifurcation Paradox: The Final State Is Predictable If the Transition Is Fast Enough.- 4 Prediction of Biological Systems.- Models and Predictability of Biological Systems.- Limits of Predictability for Biospheric Processes.- 5 Analysis and Forecasting of Financial Data.- The Application of Wave Form Dictionaries to Stock Market Index Data.- 6 Socio-Political and Global Problems.- Messy Futures and Global Brains.
This book addresses researchers and practitioners interested in modelling, 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 presenting topics like characterization of nonlinear correlations in data as dynamical systems, reconstruction of dynamical models from data, nonlinear noise reduction and the limits of predicatability. The authors consider practical problems from e.g. signal and time series analysis, biomedical data analysis, financial analysis, stochastic modelling, human evolution, and political modelling. They give new methods for nonlinear filtering of complex signals and new algorithms for signal calssification, and the concept of the 'Global Bra