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Ziel dieser Arbeit ist die Überwindung einer Differenz, die zwischen der Theorie der Phase bzw. der Phasendynamik und ihrer Anwendung in der Zeitreihenanalyse besteht: Während die theoretische Phase eindeutig bestimmt und invariant unter Koordinatentransformationen bzw. gegenüber der jeweils gewählten Observable ist, führen die Standardmethoden zur Abschätzung der Phase aus gegebenen Zeitreihen zu Resultaten, die einerseits von den gewählten Observablen abhängen und so andererseits das jeweilige System keineswegs in eindeutiger und invarianter Weise beschreiben. Um diese Differenz deutlich zu machen, wird die terminologische Unterscheidung von Phase und Protophase eingeführt: Der Terminus Phase wird nur für Variablen verwendet, die dem theoretischen Konzept der Phase entsprechen und daher das jeweilige System in invarianter Weise charakterisieren, während die observablen-abhängigen Abschätzungen der Phase aus Zeitreihen als Protophasen bezeichnet werden. Der zentrale Gegenstand dieser Arbeit ist die Entwicklung einer deterministischen Transformation, die von jeder Protophase eines selbsterhaltenden Oszillators zur eindeutig bestimmten Phase führt. Dies ermöglicht dann die invariante Beschreibung gekoppelter Oszillatoren und ihrer Wechselwirkung. Die Anwendung der Transformation bzw. ihr Effekt wird sowohl an numerischen Beispielen demonstriert - insbesondere wird die Phasentransformation in einem Beispiel auf den Fall von drei gekoppelten Oszillatoren erweitert - als auch an multivariaten Messungen des EKGs, des Pulses und der Atmung, aus denen Phasenmodelle der kardiorespiratorischen Wechselwirkung rekonstruiert werden. Abschließend wird die Phasentransformation für autonome Oszillatoren auf den Fall einer nicht vernachlässigbaren Amplitudenabhängigkeit der Protophase erweitert, was beispielsweise die numerischen Bestimmung der Isochronen des chaotischen Rössler Systems ermöglicht.
In a classical context, synchronization means adjustment of rhythms of self-sustained periodic oscillators due to their weak interaction. The history of synchronization goes back to the 17th century when the famous Dutch scientist Christiaan Huygens reported on his observation of synchronization of pendulum clocks: when two such clocks were put on a common support, their pendula moved in a perfect agreement. In rigorous terms, it means that due to coupling the clocks started to oscillate with identical frequencies and tightly related phases. Being, probably, the oldest scientifically studied nonlinear effect, synchronization was understood only in 1920-ies when E. V. Appleton and B. Van der Pol systematically - theoretically and experimentally - studied synchronization of triode generators. Since that the theory was well developed and found many applications. Nowadays it is well-known that certain systems, even rather simple ones, can exhibit chaotic behaviour. It means that their rhythms are irregular, and cannot be characterized only by one frequency. However, as is shown in the Habilitation work, one can extend the notion of phase for systems of this class as well and observe their synchronization, i.e., agreement of their (still irregular!) rhythms: due to very weak interaction there appear relations between the phases and average frequencies. This effect, called phase synchronization, was later confirmed in laboratory experiments of other scientific groups. Understanding of synchronization of irregular oscillators allowed us to address important problem of data analysis: how to reveal weak interaction between the systems if we cannot influence them, but can only passively observe, measuring some signals. This situation is very often encountered in biology, where synchronization phenomena appear on every level - from cells to macroscopic physiological systems; in normal states as well as in severe pathologies. With our methods we found that cardiovascular and respiratory systems in humans can adjust their rhythms; the strength of their interaction increases with maturation. Next, we used our algorithms to analyse brain activity of Parkinsonian patients. The results of this collaborative work with neuroscientists show that different brain areas synchronize just before the onset of pathological tremor. Morevoever, we succeeded in localization of brain areas responsible for tremor generation.
Subject of this work is the investigation of generic synchronization phenomena in interacting complex systems. These phenomena are observed, among all, in coupled deterministic chaotic systems. At very weak interactions between individual systems a transition to a weakly coherent behavior of the systems can take place. In coupled continuous time chaotic systems this transition manifests itself with the effect of phase synchronization, in coupled chaotic discrete time systems with the effect of non-vanishing macroscopic mean field. Transition to coherence in a chain of locally coupled oscillators described with phase equations is investigated with respect to the symmetries in the system. It is shown that the reversibility of the system caused by these symmetries results to non-trivial topological properties of trajectories so that the system constructed to be dissipative reveals in a whole parameter range quasi-Hamiltonian features, i.e. the phase volume is conserved on average and Lyapunov exponents come in symmetric pairs. Transition to coherence in an ensemble of globally coupled chaotic maps is described with the loss of stability of the disordered state. The method is to break the self-consistensy of the macroscopic field and to characterize the ensemble in analogy to an amplifier circuit with feedback with a complex linear transfer function. This theory is then generalized for several cases of theoretic interest.