TY - THES A1 - Zou, Yong T1 - Exploring recurrences in quasiperiodic systems T1 - Untersuchung des Wiederkehrverhaltens in quasiperiodischen dynamischen Systemen N2 - In this work, some new results to exploit the recurrence properties of quasiperiodic dynamical systems are presented by means of a two dimensional visualization technique, Recurrence Plots(RPs). Quasiperiodicity is the simplest form of dynamics exhibiting nontrivial recurrences, which are common in many nonlinear systems. The concept of recurrence was introduced to study the restricted three body problem and it is very useful for the characterization of nonlinear systems. I have analyzed in detail the recurrence patterns of systems with quasiperiodic dynamics both analytically and numerically. Based on a theoretical analysis, I have proposed a new procedure to distinguish quasiperiodic dynamics from chaos. This algorithm is particular useful in the analysis of short time series. Furthermore, this approach demonstrates to be efficient in recognizing regular and chaotic trajectories of dynamical systems with mixed phase space. Regarding the application to real situations, I have shown the capability and validity of this method by analyzing time series from fluid experiments. N2 - In dieser Arbeit stelle ich neue Resultate vor, welche zeigen, wie man Rekurrenzeigenschaften quasiperiodischer, dynamischer Systeme für eine Datenanalyse ausnutzen kann. Die vorgestellten Algorithmen basieren auf einer zweidimensionalen Darstellungsmethode, den Rekurrenz-Darstellungen. Quasiperiodizität ist die einfachste Dynamik, die nicht-triviale Rekurrenzen zeigt und tritt häufig in nichtlinearen Systemen auf. Nicht-triviale Rekurrenzen wurden im Zusammenhang mit dem eingeschränkten Dreikörper-problem eingeführt. In dieser Arbeit, habe ich mehrere Systeme mit quasiperiodischem Verhalten analytisch untersucht. Die erhaltenen Ergebnisse helfen die Wiederkehreigenschaften dieser Systeme im Detail zu verstehen. Basierend auf den analytischen Resultaten, schlage ich einen neuen Algorithmus vor, mit dessen Hilfe selbst in kurzen Zeitreihen zwischen chaotischem und quasiperiodischem Verhalten unterschieden werden kann. Die vorgeschlagene Methode ist besonders effizient zur Unterscheidung regulärer und chaotischer Trajektorien mischender dynamischer Systeme.Die praktische Anwendbarkeit der vorgeschlagenen Analyseverfahren auf Messdaten, habe ich gezeigt, indem ich erfolgreich Zeitreihen aus fluid-dynamischen Experimenten untersucht habe. KW - Wiederkehrverhalten KW - quasiperiodisches dynamisches System KW - Recurrence Plot KW - recurrence KW - quasiperiodic dynamical systems KW - recurrence plots Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-16497 ER - TY - THES A1 - Thiel, Marco T1 - Recurrences : exploiting naturally occurring analogues N2 - In der vorliegenden Arbeit wird die Wiederkehr im Phasenraum ausgenutzt. Dabei werden drei Hauptresultate besprochen. 1. Die Wiederkehr erlaubt die Vorhersagbarkeit des Systems zu quantifizieren. 2. Die Wiederkehr enthaelt (unter bestimmten Voraussetzungen) sämtliche relevante Information über die Dynamik im Phasenraum 3. Die Wiederkehr erlaubt die Erzeugung dynamischer Ersatzdaten. N2 - Recurrence plots, a rather promising tool of data analysis, have been introduced by Eckman et al. in 1987. They visualise recurrences in phase space and give an overview about the system's dynamics. Two features have made the method rather popular. Firstly they are rather simple to compute and secondly they are putatively easy to interpret. However, the straightforward interpretation of recurrence plots for some systems yields rather surprising results. For example indications of low dimensional chaos have been reported for stock marked data, based on recurrence plots. In this work we exploit recurrences or ``naturally occurring analogues'' as they were termed by E. Lorenz, to obtain three key results. One of which is that the most striking structures which are found in recurrence plots are hinged to the correlation entropy and the correlation dimension of the underlying system. Even though an eventual embedding changes the structures in recurrence plots considerably these dynamical invariants can be estimated independently of the special parameters used for the computation. The second key result is that the attractor can be reconstructed from the recurrence plot. This means that it contains all topological information of the system under question in the limit of long time series. The graphical representation of the recurrences can also help to develop new algorithms and exploit specific structures. This feature has helped to obtain the third key result of this study. Based on recurrences to points which have the same ``recurrence structure'', it is possible to generate surrogates of the system which capture all relevant dynamical characteristics, such as entropies, dimensions and characteristic frequencies of the system. These so generated surrogates are shadowed by a trajectory of the system which starts at different initial conditions than the time series in question. They can be used then to test for complex synchronisation. T2 - Recurrences : exploiting naturally occurring analogues KW - Wiederkehrdiagramme KW - Rekurrenzen KW - Datenanalyse KW - Surrogates KW - recurrence plots KW - recurrences KW - data analysis KW - surrogates Y1 - 2004 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-0001633 ER -