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Replication of Chaos in Neural Networks, Economics and Physics

This book presents detailed descriptions of chaos for continuous-time systems. It is the first-ever book to consider chaos as an input for differential and hybrid equations. Chaotic sets and chaotic functions are used as inputs for systems with attractors: equilibrium points, cycles and tori. The fi...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Akhmet, Marat (Autor), Fen, Mehmet Onur (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:Nonlinear Physical Science,
Temas:
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Replication of Chaos in Neural Networks, Economics and Physics  |h [electronic resource] /  |c by Marat Akhmet, Mehmet Onur Fen. 
250 |a 1st ed. 2016. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2016. 
300 |a XV, 457 p. 141 illus., 133 illus. in color.  |b online resource. 
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490 1 |a Nonlinear Physical Science,  |x 1867-8459 
505 0 |a Introduction -- Replication of Continuous Chaos about Equilibria -- Chaos Extension in Hyperbolic Systems -- Entrainment by Chaos -- Chaotification of Impulsive Systems by Perturbations -- Chaos Generation in Continuous/Discrete-Time Models -- Economic Models with Deterministic Chaos as Generated by Exogenous Continuous/Discrete Shocks -- Replication of Chaos by Neural Networks -- ntrainment by Spatiotemporal Chaos in Glow Discharge-Semiconductor Systems. 
520 |a This book presents detailed descriptions of chaos for continuous-time systems. It is the first-ever book to consider chaos as an input for differential and hybrid equations. Chaotic sets and chaotic functions are used as inputs for systems with attractors: equilibrium points, cycles and tori. The findings strongly suggest that chaos theory can proceed from the theory of differential equations to a higher level than previously thought. The approach selected is conducive to the in-depth analysis of different types of chaos. The appearance of deterministic chaos in neural networks, economics and mechanical systems is discussed theoretically and supported by simulations. As such, the book offers a valuable resource for mathematicians, physicists, engineers and economists studying nonlinear chaotic dynamics. 
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650 0 |a Biomathematics. 
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650 2 4 |a Engineering Mechanics. 
650 2 4 |a Quantitative Economics. 
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