Extracting Knowledge From Time Series An Introduction to Nonlinear Empirical Modeling /

This book addresses the fundamental question of how to construct mathematical models for the evolution of dynamical systems from experimentally-obtained time series. It places emphasis on chaotic signals and nonlinear modeling and discusses different approaches to the forecast of future system evolu...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Bezruchko, Boris P. (Autor), Smirnov, Dmitry A. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Edición:1st ed. 2010.
Colección:Springer Series in Synergetics,
Temas:
System theory.
Geophysics.
Social sciences-Mathematics.
Econometrics.
Environmental sciences.
Physics.
Mathematical physics.
Complex Systems.
Mathematics in Business, Economics and Finance.
Quantitative Economics.
Environmental Physics.
Theoretical, Mathematical and Computational Physics.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Models And Forecast
  • The Concept of Model. What is Remarkable in Mathematical Models
  • Two Approaches to Modelling and Forecast
  • Dynamical (Deterministic) Models of Evolution
  • Stochastic Models of Evolution
  • Modeling From Time Series
  • Problem Posing in Modelling from Data Series
  • Data Series as a Source for Modelling
  • Restoration of Explicit Temporal Dependencies
  • Model Equations: Parameter Estimation
  • Model Equations: Restoration of Equivalent Characteristics
  • Model Equations: "Black Box" Reconstruction
  • Practical Applications of Empirical Modelling
  • Identification of Directional Couplings
  • Outdoor Examples.

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