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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Bezruchko, Boris P. (Συγγραφέας), Smirnov, Dmitry A. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Σειρά:Springer Series in Synergetics,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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020 |a 9783642126017  |9 978-3-642-12601-7 
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100 1 |a Bezruchko, Boris P.  |e author. 
245 1 0 |a Extracting Knowledge From Time Series  |h [electronic resource] :  |b An Introduction to Nonlinear Empirical Modeling /  |c by Boris P. Bezruchko, Dmitry A. Smirnov. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2010. 
300 |a XXII, 410 p. 162 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Springer Series in Synergetics,  |x 0172-7389 
505 0 |a 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. 
520 |a 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 evolution. In particular, it teaches readers how to construct difference and differential model equations depending on the amount of a priori information that is available on the system in addition to the experimental data sets. This book will benefit graduate students and researchers from all natural sciences who seek a self-contained and thorough introduction to this subject. 
650 0 |a Physics. 
650 0 |a Geophysics. 
650 0 |a Economics, Mathematical. 
650 0 |a Statistical physics. 
650 0 |a Dynamical systems. 
650 0 |a Environmental sciences. 
650 0 |a Economic theory. 
650 1 4 |a Physics. 
650 2 4 |a Statistical Physics, Dynamical Systems and Complexity. 
650 2 4 |a Geophysics/Geodesy. 
650 2 4 |a Quantitative Finance. 
650 2 4 |a Economic Theory/Quantitative Economics/Mathematical Methods. 
650 2 4 |a Environmental Physics. 
700 1 |a Smirnov, Dmitry A.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783642126000 
830 0 |a Springer Series in Synergetics,  |x 0172-7389 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-12601-7  |z Full Text via HEAL-Link 
912 |a ZDB-2-PHA 
950 |a Physics and Astronomy (Springer-11651)