Buch, Englisch, 386 Seiten, Format (B × H): 170 mm x 244 mm, Gewicht: 668 g
Buch, Englisch, 386 Seiten, Format (B × H): 170 mm x 244 mm, Gewicht: 668 g
ISBN: 978-0-521-52902-0
Verlag: Cambridge University Press
The paradigm of deterministic chaos has influenced thinking in many fields of science. Chaotic systems show rich and surprising mathematical structures. In the applied sciences, deterministic chaos provides a striking explanation for irregular behaviour and anomalies in systems which do not seem to be inherently stochastic. The most direct link between chaos theory and the real world is the analysis of time series from real systems in terms of nonlinear dynamics. Experimental technique and data analysis have seen such dramatic progress that, by now, most fundamental properties of nonlinear dynamical systems have been observed in the laboratory. Great efforts are being made to exploit ideas from chaos theory wherever the data displays more structure than can be captured by traditional methods. Problems of this kind are typical in biology and physiology but also in geophysics, economics, and many other sciences.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
- Naturwissenschaften Physik Quantenphysik
- Naturwissenschaften Physik Physik Allgemein Geschichte der Physik
- Naturwissenschaften Physik Physik Allgemein Experimentalphysik
- Naturwissenschaften Physik Physik Allgemein Theoretische Physik, Mathematische Physik, Computerphysik
- Naturwissenschaften Physik Angewandte Physik Statistische Physik, Dynamische Systeme
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
Weitere Infos & Material
Preface; Acknowledgements; Part I. Basic Topics: 1. Introduction: why nonlinear methods?; 2. Linear tools and general considerations; 3. Phase space methods; 4. Determinism and predictability; 5. Instability: Lyapunov exponents; 6. Self-similarity: dimensions; 7. Using nonlinear methods when determinism is weak; 8. Selected nonlinear phenomena; Part II. Advanced Topics: 9. Advanced embedding methods; 10. Chaotic data and noise; 11. More about invariant quantities; 12. Modelling and forecasting; 13. Non-stationary signals; 14. Coupling and synchronisation of nonlinear systems; 15. Chaos control; Appendix A: using the TISEAN programs; Appendix B: description of the experimental data sets; References; Index.
