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Predictability of Complex Dynamical Systems

  • Book
  • © 1996

Overview

Editors:
  1. Yurii A. Kravtsov

    1. Space Research Institute, Russian Academy of Sciences, Moscow, Russia

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    You can also search for this editor in PubMed   Google Scholar

  2. James B. Kadtke

    1. Institute for Pure and Applied Physical Sciences, University of California at San Diego, La Jolla, USA

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    You can also search for this editor in PubMed   Google Scholar

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

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Table of contents (12 chapters)

  1. Front Matter

    Pages I-XII
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  2. Introduction

    1. Front Matter

      Pages 1-1
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    2. Introduction

      • James B. Kadtke, Yurii A. Kravtsov
      Pages 3-20

  3. Time Series Analysis: The Search for Determinism

    1. Front Matter

      Pages 21-21
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    2. Method to Discriminate Against Determinism in Time Series Data

      • Robert Cawley, Guan-Hsong Hsu, Liming W. Salvino
      Pages 23-41

    3. Observing and Predicting Chaotic Signals: Is 2% Noise Too Much?

      • Thomas Schreiber, Holger Kantz
      Pages 43-65

    4. A Discriminant Procedure for the Solution of Inverse Problems for Nonstationary Systems

      • Oleg L. Anosov, Oleg Ya. Butkovskii
      Pages 67-77

    5. Classifying Complex, Deterministic Signals

      • James B. Kadtke, Michael Kremliovsky
      Pages 79-102

  4. Dynamical Modeling and Forecasting Algorithms

    1. Front Matter

      Pages 103-103
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    2. Strategy and Algorithms for Dynamical Forecasting

      • Oleg L. Anosov, Oleg Ya. Butkovskii, Yurii A. Kravtsov
      Pages 105-121

    3. Parsimony in Dynamical Modeling

      • Alistair I. Mees, Kevin Judd
      Pages 123-141

    4. The Bifurcation Paradox: The Final State is Predictable If the Transition Is Fast Enough

      • Oleg Ya. Butkovskii, Yurii A. Kravtsov, Jeffrey S. Brush
      Pages 143-150

  5. Prediction of Biological Systems

    1. Front Matter

      Pages 151-151
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    2. Models and Predictability of Biological Systems

      • Martin P. Paulus
      Pages 153-168

    3. Limits of Predictability for Biospheric Processes

      • Nikita N. Moiseev
      Pages 169-185

  6. Analysis and Forecasting of Financial Data

    1. Front Matter

      Pages 187-187
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    2. The Application of Wave Form Dictionaries to Stock Market Index Data

      • James B. Ramsey, Zhifeng Zhang
      Pages 189-205

  7. Socio-Political and Global Problems

    1. Front Matter

      Pages 207-207
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    2. Messy Futures and Global Brains

      • Gottfried Mayer-Kress
      Pages 209-232

  8. Back Matter

    Pages 233-234
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Keywords

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".

Editors and Affiliations

  • Space Research Institute, Russian Academy of Sciences, Moscow, Russia

    Yurii A. Kravtsov

  • Institute for Pure and Applied Physical Sciences, University of California at San Diego, La Jolla, USA

    James B. Kadtke

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