000			03150nam a22005295i 4500
001			978-3-642-12601-7
003			DE-He213
005			20140220084535.0
007			cr nn 008mamaa
008			100907s2010 gw | s |||| 0|eng d
020			_a9783642126017 _9978-3-642-12601-7
024	7		_a10.1007/978-3-642-12601-7 _2doi
050		4	_aQC174.7-175.36
072		7	_aPHS _2bicssc
072		7	_aPHDT _2bicssc
072		7	_aSCI055000 _2bisacsh
082	0	4	_a621 _223
100	1		_aBezruchko, Boris P. _eauthor.
245	1	0	_aExtracting Knowledge From Time Series _h[electronic resource] : _bAn Introduction to Nonlinear Empirical Modeling / _cby Boris P. Bezruchko, Dmitry A. Smirnov.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2010.
300			_aXXII, 410 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringer Series in Synergetics, _x0172-7389
505	0		_aModels 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			_aThis 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	_aPhysics.
650		0	_aPhysical geography.
650		0	_aFinance.
650		0	_aEconomics, Mathematical.
650	1	4	_aPhysics.
650	2	4	_aStatistical Physics, Dynamical Systems and Complexity.
650	2	4	_aGeophysics/Geodesy.
650	2	4	_aQuantitative Finance.
650	2	4	_aGame Theory/Mathematical Methods.
650	2	4	_aEnvironmental Physics.
700	1		_aSmirnov, Dmitry A. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642126000
830		0	_aSpringer Series in Synergetics, _x0172-7389
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-12601-7
912			_aZDB-2-PHA
999			_c112106 _d112106