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Complex and adaptive dynamical systems = a comprehensive introduction /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Complex and adaptive dynamical systems/ by Claudius Gros.
其他題名:	a comprehensive introduction /
作者:	Gros, Claudius.
出版者:	Cham :Springer International Publishing : : 2024.,
面頁冊數:	xv, 461 p. :ill., digital ;24 cm.
內容註:	Network Theory -- Bifurcations and Chaos in Dynamical Systems -- Dissipation, Noise and Adaptive Systems -- Self Organization -- Information Theory of Complex Systems -- Self-Organized Criticality -- Random Boolean Networks -- Darwinian Evolution, Hypercycles and Game Theory -- Synchronization Phenomena -- Complexity of Machine Learning -- Solutions.
Contained By:	Springer Nature eBook
標題:	Differentiable dynamical systems. -
電子資源:	https://doi.org/10.1007/978-3-031-55076-8
ISBN:	9783031550768

Complex and adaptive dynamical systems = a comprehensive introduction /
Gros, Claudius.

Complex and adaptive dynamical systemsa comprehensive introduction /[electronic resource] :by Claudius Gros. - Fifth edition. - Cham :Springer International Publishing :2024. - xv, 461 p. :ill., digital ;24 cm.

Network Theory -- Bifurcations and Chaos in Dynamical Systems -- Dissipation, Noise and Adaptive Systems -- Self Organization -- Information Theory of Complex Systems -- Self-Organized Criticality -- Random Boolean Networks -- Darwinian Evolution, Hypercycles and Game Theory -- Synchronization Phenomena -- Complexity of Machine Learning -- Solutions.

This textbook offers a comprehensive introduction to the concepts underpinning our modern understanding of complex and emergent behavior. Mathematical methods necessary for the discussion are introduced and explained on the run. All derivations are presented step-by-step. This new fifth edition has been fully revised and includes a new chapter, a range of new sections, figures and exercises. The Solution chapter has been reorganized for clarity. The core aspects of modern complex system sciences are presented in the first chapters, covering the foundations of network- and dynamical system theory, with a particular focus on scale-free networks and tipping phenomena. The notion of deterministic chaos is treated together with bifurcation theory and the intricacies of time delays. Modern information theoretical principles are discussed in further chapters, together with the notion of self-organized criticality, synchronization phenomena, and a game-theoretical treatment of the tragedy of the commons. The dynamical systems view of modern machine learning is presented in a new chapter. Chapters include exercises and suggestions for further reading. The textbook is suitable for graduate and advanced undergraduate students. The prerequisites are the basic mathematical tools of courses in natural sciences, computer science or engineering.

ISBN: 9783031550768

Standard No.: 10.1007/978-3-031-55076-8doiSubjects--Topical Terms:

524351
Differentiable dynamical systems.

LC Class. No.: QA614.8 / .G76 2024

Dewey Class. No.: 515.352

Complex and adaptive dynamical systems = a comprehensive introduction /
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520 $a This textbook offers a comprehensive introduction to the concepts underpinning our modern understanding of complex and emergent behavior. Mathematical methods necessary for the discussion are introduced and explained on the run. All derivations are presented step-by-step. This new fifth edition has been fully revised and includes a new chapter, a range of new sections, figures and exercises. The Solution chapter has been reorganized for clarity. The core aspects of modern complex system sciences are presented in the first chapters, covering the foundations of network- and dynamical system theory, with a particular focus on scale-free networks and tipping phenomena. The notion of deterministic chaos is treated together with bifurcation theory and the intricacies of time delays. Modern information theoretical principles are discussed in further chapters, together with the notion of self-organized criticality, synchronization phenomena, and a game-theoretical treatment of the tragedy of the commons. The dynamical systems view of modern machine learning is presented in a new chapter. Chapters include exercises and suggestions for further reading. The textbook is suitable for graduate and advanced undergraduate students. The prerequisites are the basic mathematical tools of courses in natural sciences, computer science or engineering.
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