東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ subject:"Chaotic behavior in systems- Mathematical models." ]

切換: 標籤 | MARC模式 | ISBD

Predictability of chaotic dynamics =...

Vallejo, Juan C.

FindBook

Google Book

Amazon

博客來

Predictability of chaotic dynamics = a finite-time Lyapunov exponents approach /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Predictability of chaotic dynamics/ by Juan C. Vallejo, Miguel A. F. Sanjuan.
其他題名:	a finite-time Lyapunov exponents approach /
作者:	Vallejo, Juan C.
其他作者:	Sanjuan, Miguel A. F.
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	xix, 196 p. :ill. (some col.), digital ;24 cm.
內容註:	Preface -- Forecasting and chaos -- Lyapunov exponents -- Dynamical regimes and timescales -- Predictability -- Chaos, predictability and astronomy -- A detailed example: galactic dynamics -- Appendix.
Contained By:	Springer eBooks
標題:	Chaotic behavior in systems - Mathematical models. -
電子資源:	https://doi.org/10.1007/978-3-030-28630-9
ISBN:	9783030286309

Predictability of chaotic dynamics = a finite-time Lyapunov exponents approach /
Vallejo, Juan C.

Predictability of chaotic dynamicsa finite-time Lyapunov exponents approach /[electronic resource] :by Juan C. Vallejo, Miguel A. F. Sanjuan. - 2nd ed. - Cham :Springer International Publishing :2019. - xix, 196 p. :ill. (some col.), digital ;24 cm. - Springer series in synergetics,0172-7389. - Springer series in synergetics..

Preface -- Forecasting and chaos -- Lyapunov exponents -- Dynamical regimes and timescales -- Predictability -- Chaos, predictability and astronomy -- A detailed example: galactic dynamics -- Appendix.

This book is primarily concerned with the computational aspects of predictability of dynamical systems - in particular those where observations, modeling and computation are strongly interdependent. Unlike with physical systems under control in laboratories, in astronomy it is uncommon to have the possibility of altering the key parameters of the studied objects. Therefore, the numerical simulations offer an essential tool for analysing these systems, and their reliability is of ever-increasing interest and importance. In this interdisciplinary scenario, the underlying physics provide the simulated models, nonlinear dynamics provides their chaoticity and instability properties, and the computer sciences provide the actual numerical implementation. This book introduces and explores precisely this link between the models and their predictability characterization based on concepts derived from the field of nonlinear dynamics, with a focus on the strong sensitivity to initial conditions and the use of Lyapunov exponents to characterize this sensitivity. This method is illustrated using several well-known continuous dynamical systems, such as the Contopoulos, Henon-Heiles and Rössler systems. This second edition revises and significantly enlarges the material of the first edition by providing new entry points for discussing new predictability issues on a variety of areas such as machine decision-making, partial differential equations or the analysis of attractors and basins. Finally, the parts of the book devoted to the application of these ideas to astronomy have been greatly enlarged, by first presenting some basics aspects of predictability in astronomy and then by expanding these ideas to a detailed analysis of a galactic potential.

ISBN: 9783030286309

Standard No.: 10.1007/978-3-030-28630-9doiSubjects--Topical Terms:

858820
Chaotic behavior in systems
--Mathematical models.

LC Class. No.: Q172.5.C45 / V355 2019

Dewey Class. No.: 003.857

Predictability of chaotic dynamics = a finite-time Lyapunov exponents approach /
LDR:03109nmm a2200361 a 4500 001 2219088
003 DE-He213
005 20200131153536.0
006 m d
007 cr nn 008maaau
008 201126s2019 sz s 0 eng d
020 $a 9783030286309 $q (electronic bk.)
020 $a 9783030286293 $q (paper)
024 7 $a 10.1007/978-3-030-28630-9 $2 doi
035 $a 978-3-030-28630-9
040 $a GP $c GP
041 0 $a eng
050 4 $a Q172.5.C45 $b V355 2019
072 7 $a PBWR $2 bicssc
072 7 $a SCI012000 $2 bisacsh
072 7 $a PBWR $2 thema
072 7 $a PHDT $2 thema
082 0 4 $a 003.857 $2 23
090 $a Q172.5.C45 $b V182 2019
100 1 $a Vallejo, Juan C. $3 3227628
245 1 0 $a Predictability of chaotic dynamics $h [electronic resource] : $b a finite-time Lyapunov exponents approach / $c by Juan C. Vallejo, Miguel A. F. Sanjuan.
250 $a 2nd ed.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xix, 196 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Springer series in synergetics, $x 0172-7389
505 0 $a Preface -- Forecasting and chaos -- Lyapunov exponents -- Dynamical regimes and timescales -- Predictability -- Chaos, predictability and astronomy -- A detailed example: galactic dynamics -- Appendix.
520 $a This book is primarily concerned with the computational aspects of predictability of dynamical systems - in particular those where observations, modeling and computation are strongly interdependent. Unlike with physical systems under control in laboratories, in astronomy it is uncommon to have the possibility of altering the key parameters of the studied objects. Therefore, the numerical simulations offer an essential tool for analysing these systems, and their reliability is of ever-increasing interest and importance. In this interdisciplinary scenario, the underlying physics provide the simulated models, nonlinear dynamics provides their chaoticity and instability properties, and the computer sciences provide the actual numerical implementation. This book introduces and explores precisely this link between the models and their predictability characterization based on concepts derived from the field of nonlinear dynamics, with a focus on the strong sensitivity to initial conditions and the use of Lyapunov exponents to characterize this sensitivity. This method is illustrated using several well-known continuous dynamical systems, such as the Contopoulos, Henon-Heiles and Rössler systems. This second edition revises and significantly enlarges the material of the first edition by providing new entry points for discussing new predictability issues on a variety of areas such as machine decision-making, partial differential equations or the analysis of attractors and basins. Finally, the parts of the book devoted to the application of these ideas to astronomy have been greatly enlarged, by first presenting some basics aspects of predictability in astronomy and then by expanding these ideas to a detailed analysis of a galactic potential.
650 0 $a Chaotic behavior in systems $x Mathematical models. $3 858820
650 1 4 $a Applications of Nonlinear Dynamics and Chaos Theory. $3 3134772
650 2 4 $a Numerical and Computational Physics, Simulation. $3 2209853
650 2 4 $a Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics) $3 3217206
650 2 4 $a Mathematical Applications in the Physical Sciences. $3 1566152
700 1 $a Sanjuan, Miguel A. F. $3 3299069
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Springer series in synergetics. $3 1568157
856 4 0 $u https://doi.org/10.1007/978-3-030-28630-9
950 $a Physics and Astronomy (Springer-11651)