Predictability of Complex Dynamical Systems

  • Yurii A. Kravtsov
  • James B. Kadtke

Part of the Springer Series in Synergetics book series (SSSYN, volume 69)

Table of contents

  1. Front Matter
    Pages I-XII
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. James B. Kadtke, Yurii A. Kravtsov
      Pages 3-20
  3. Time Series Analysis: The Search for Determinism

    1. Front Matter
      Pages 21-21
    2. Robert Cawley, Guan-Hsong Hsu, Liming W. Salvino
      Pages 23-41
    3. Thomas Schreiber, Holger Kantz
      Pages 43-65
    4. James B. Kadtke, Michael Kremliovsky
      Pages 79-102
  4. Dynamical Modeling and Forecasting Algorithms

    1. Front Matter
      Pages 103-103
    2. Oleg L. Anosov, Oleg Ya. Butkovskii, Yurii A. Kravtsov
      Pages 105-121
    3. Alistair I. Mees, Kevin Judd
      Pages 123-141
    4. Oleg Ya. Butkovskii, Yurii A. Kravtsov, Jeffrey S. Brush
      Pages 143-150
  5. Prediction of Biological Systems

    1. Front Matter
      Pages 151-151
    2. Martin P. Paulus
      Pages 153-168
    3. Nikita N. Moiseev
      Pages 169-185
  6. Analysis and Forecasting of Financial Data

    1. Front Matter
      Pages 187-187
    2. James B. Ramsey, Zhifeng Zhang
      Pages 189-205
  7. Socio-Political and Global Problems

    1. Front Matter
      Pages 207-207
    2. Gottfried Mayer-Kress
      Pages 209-232
  8. Back Matter
    Pages 233-234

About this book


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".


Chaos Predictability Synergetics algorithms complex systems dynamical systems forecasting modeling nonlinear dynamics strategy time series analysis

Editors and affiliations

  • Yurii A. Kravtsov
    • 1
  • James B. Kadtke
    • 2
  1. 1.Space Research InstituteRussian Academy of SciencesMoscowRussia
  2. 2.Institute for Pure and Applied Physical SciencesUniversity of California at San DiegoLa JollaUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 1996
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-80256-0
  • Online ISBN 978-3-642-80254-6
  • Series Print ISSN 0172-7389
  • Buy this book on publisher's site