Replication of Chaos in Neural Networks, Economics and Physics
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2016
Abstract/Sommario:
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 ...; [leggi tutto]
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| Descrizione | Replication of Chaos in Neural Networks, Economics and Physics / by Marat Akhmet, Mehmet Onur Fen. - 1st ed. 2016. - Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2016. - XV, 457 p. 141 ill., 133 ill. in color ; online resource. - (Nonlinear Physical Science) |
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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. - Springer eBooks. - Printed edition: 9783662474990
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| ID scheda | 139496 |
| Permalink | https://www.opac.inaf.it/?ids=139496 |